Global Risks Report 2013

Transcription

Insight Report
Global Risks 2013
Eighth Edition
An Initiative of the Risk Response Network
The information in this report, or on which this report
is based, has been obtained from sources that the
authors believe to be reliable and accurate. However,
it has not been independently verified and no
representation or warranty, express or implied, is made
as to the accuracy or completeness of any information
obtained from third parties. In addition, the statements
in this report may provide current expectations of future
events based on certain assumptions and include any
statement that does not directly relate to a historical fact
or a current fact. These statements involve known and
unknown risks, uncertainties and other factors which
are not exhaustive. The companies contributing to this
report operate in a continually changing environment
and new risks emerge continually. Readers are
cautioned not to place undue reliance on these
statements. The companies contributing to this report
undertake no obligation to publicly revise or update
any statements, whether as a result of new information,
future events or otherwise and they shall in no event be
liable for any loss or damage arising in connection with
the use of the information in this report.
© 2013 World Economic Forum
All rights reserved.
No part of this publication may be reproduced or
transmitted in any form or by any means, including
photocopying and recording, or by any information
storage and retrieval system.
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2
Global Risks 2013
Global Risks 2013
Eighth Edition
An Initiative of the Risk Response Network
Lee Howell
Editor in Chief
World Economic Forum in collaboration with:
Marsh & McLennan Companies
National University of Singapore
Oxford Martin School, University of Oxford
Swiss Reinsurance Company
Wharton Center for Risk Management, University of Pennsylvania
Zurich Insurance Group
Global Risks 2013
3
Figure 1: Global Risks Landscape 2013 versus 2012i
Economic
Environmental
Major systemic financial failure
Chronic fiscal imbalances
4
4
Extreme volatility in energy
and agriculture prices
Failure of climate change adaptation
Severe income
disparity
Recurring liquidity crises
Unmanageable
inflation or deflation
Irremediable pollution
Chronic labour
market imbalances
3.5
Antibiotic-resistant
bacteria
Unprecedented
geophysical
destruction
3
Unforeseen negative consequences of regulation
2.5
3
3.5
Impact if the risk were to occur
Prolonged infrastructure neglect
Rising
greenhouse
gas emissions
Land and waterway
use mismanagement
3.5
Hard landing of an
emerging economy
2.5
Persistent
extreme
weather
Mismanaged urbanization
Species overexploitation
Vulnerability to
geomagnetic storms
3
2.5
4
2.5
Likelihood to occur in the next ten years
3
3.5
4
Geopolitical
Societal
4
Water supply crises
4
Diffusion of weapons
of mass destruction
Food shortage crises
Global governance failure
Rising religious fanaticism
Unsustainable population growth
Failure of diplomatic
conflict resolution
3.5
Terrorism
Critical fragile states
Unmanaged migration
Unilateral resource nationalization
Backlash against globalization
Militarization
of space
Entrenched organized crime
3
Widespread illicit trade
2.5
2.5
3
3.5
4
3
2.5
2.5
3
4
Critical systems failure
Unforeseen
consequences
of new life science
technologies
Mineral resource
supply vulnerability
Cyber attacks
Massive incident of
data fraud/theft
Massive digital misinformation
Unforeseen consequences
of climate change mitigation
3
Unforeseen
consequences
of nanotechnology
Failure of intellectual property regime
Proliferation of orbital debris
2.5
2.5
3
3.5
4
Source: World Economic Forum
i
4
NB: Some of the movements are due to changes in the composition of the sample. For more detail please see Section 4 Survey Findings.
Global Risks 2013
Rising rates of chronic disease
Ineffective illicit drug policies
Technological
3.5
Mismanagement of
population ageing
Vulnerability to pandemics
3.5
Pervasive entrenched
corruption
3.5
4
Figure 2: Global Risks Landscape 2013
4.2
4.1
4
Water supply crises
Diffusion of weapons of mass destruction
3.9
Rising greenhouse gas emissions
Extreme volatility in energy and agriculture prices
3.8
Severe income disparity
Chronic labour market imbalances
conflict resolution
Mismanagement of population ageing
Rising
Recurring
religious
liquidity
fanaticism
Persistent
extreme
weather
crises
Vulnerability
Terrorism
to pandemics
Unmanageable inflation or deflation
Antibioticresistant
Land and waterway
bacteria
Cyber attacks
use mismanagement
Hard landing of an emerging economy
Pervasive entrenched corruption
Mineral resource supply
vulnerability
Unforeseen consequences of new life science technologies
Unmanaged migration
3.7
3.6
3.5
3.4
3.3
Unprecedented geophysical destruction
Unforeseen
consequences
of climate
change mitigation
Rising rates of
chronic disease
Massive incident of data fraud/theft
3.2
Militarization of space
Vulnerability to
geomagnetic
storms
3.1
Prolonged
infrastructure
neglect
Unforeseen negative
consequences
of regulation
3
of nanotechnology
2.9
2.8
5
Economic
4
2.7
Environmental
3
Geopolitical
2
2.6
Societal
1
1
2
3
4
Technological
5
2.5
2.5
2.6
2.7
2.8
2.9
3
3.1
3.2
3.3
3.4
3.5
3.6
3.7
3.8
3.9
4
4.1
4.2
Global Risks 2013
5
Figure 3: Global Risks Map 2013ii
Vulnerability to geomagnetic storms
Prolonged infrastructure
neglect
Digital Wildfires in a
Hyperconnected World
Cyber attacks
Terrorism
Failure of diplomatic conflict resolution
Widespread
illicit trade
Ineffective
illicit drug
policies
Global governance
failure
Unforeseen negative
consequences of regulation
Failure of intellectual
property regime
Extreme volatility in energy
and agriculture prices
Land and waterway use
mismanagement
Mineral resource
Water supply crises
Persistent
extreme
weather
Unprecedented
geophysical
destruction
Mismanaged
urbanization
Chronic fiscal
imbalances
Unmanaged migration
Mismanagement of population aging
Rising rates of
chronic disease
Antibiotic
resistant
bacteria
Testing Economic and
Environmental Resilience
The Dangers of Hubris
on Human Health
ii
6
Please see figure 37 in Survey Findings for the complete global risks interconnection map.
Global Risks 2013
Unforeseen consequences of nanotechnology
Contents
Section 1
8
Preface
9
Foreword
10
Executive Summary
13
14
Box 1: The Evolving Risk Landscape
Introduction
Section 2
16
21
23
27
Testing Economic and Environmental Resilience
Box 2: The Green Growth Action Alliance (G2A2)
Digital Wildfires in a Hyperconnected World
Box 3: Hyperconnected World
28
The Dangers of Hubris on Human Health
34
Box 4: Bringing Space Down to Earth
Section 3
36
Special Report: Building National Resilience to Global Risks
42
Box 5: Supply Chain Risk Initiative
43
Box 6: Resilience Practices Exchange (RPE)
43
Box 7: One Year On Resilience Practices
Section 4
45
53
Survey Findings
Box 8: The Global Risks 2013 Data Explorer
Section 5
55
X Factors
60
Conclusion
Section 6
61
Appendix 1 - The Survey
62
Appendix 2 - Likelihood and Impact
66
Appendix 3 - Resilience
74
Acknowledgements
78
Project Team
Global Risks 2013
7
Section 1
Preface
Section 2
Resilient Dynamism is the theme for this
year’s World Economic Forum Annual
Meeting in Davos-Klosters, and I am
pleased to introduce the Global Risks
2013 report in the same spirit. Based on
an extensive survey of over 1,000 experts
worldwide, the report – now in its eighth
edition – serves to orient and inform
decision-makers as they seek to make
sense of an increasingly complex and
fast-changing world. I hope this report
challenges, provokes and inspires you,
and I invite you to engage – if you have not
already done so – with the World
Economic Forum’s Risk Response
Network, which provides private and
public sector leaders with a collaborative
platform to build national resilience to
global risks.
Section 3
Section 4
As we strive to restore confidence and
growth globally, leaders cannot continue
with a “risk-off” mindset if our collective
goal remains to seize transformational
opportunities that can improve the state
of the world. Dynamism in our
hyperconnected world requires
increasing our resilience to the many
global risks that loom before us.
Section 5
By their nature, global risks do not
respect national borders, as highlighted in
this report. And we now know that
extreme weather events exacerbated by
climate change will not limit their effects to
countries that are major greenhouse gas
emitters; false information posted on
social networks can spread like wildfire to
the other side of the globe in a matter of
milliseconds; and genes that make
bacteria resistant to our strongest
antibiotics can hitch a ride with patients
on an intercontinental flight.
Section 6
I, therefore, invite you to read the case
studies in this report of the three
examples cited above to understand
better the international and
interdependent nature of such
constellations of risks. I think you will
agree that each one makes a compelling
case for stronger cross-border
collaboration among stakeholders from
governments, business and civil society
– a partnership with the purpose of
building resilience to global risks. They
also highlight the need for strengthening
existing mechanisms to mitigate and
manage risks, which today primarily exist
at the national level. This means that while
we can map and describe global risks,
we cannot predict when and how they will
manifest; therefore, building national
resilience to global risks is of paramount
importance.
8
Global Risks 2013
Klaus Schwab
Founder and Executive Chairman
Section 1
Foreword
Kaplan, R.S., and Mikes, A. Managing Risks: A New
Framework. In Harvard Business Review, 2012.
Global Risks 2013
9
Section 6
1
Lee Howell
Managing Director
Risk Response Network
Section 5
The concept of resilience also influenced
this year’s Global Risks Perception
Survey, on which this report is built. The
annual survey of experts worldwide
added a new question asking respondents to rate their country’s resilience – or,
precisely, its ability to adapt and recover
– in the face of each of the 50 risks
covered in the survey. More than 1,000
experts responded to our survey, making
the dataset explored in this report more
textured and robust than ever.
Linked to this research effort is the launch
of an online “Resilience Practices
Exchange”, where leaders can learn and
contribute to building resilience using the
latest social enterprise technology. These
new efforts will enable the World Economic
Forum’s Risk Response Network (RRN) to
become the foremost international platform
to enable leaders to map, mitigate, monitor
and enhance resilience to global risks.
Therefore, I invite you to get in touch with
the RRN and share your ideas and
initiatives to assess and to improve national
resilience to global risks.
Section 4
First are “preventable” risks, such as
breakdowns in processes and mistakes by
employees. Second are “strategic” risks,
which a company undertakes voluntarily,
having weighed them against the potential
rewards. Third are “external” risks, which
this report calls “global risks”; they are
complex and go beyond a company’s
scope to manage and mitigate (i.e. they are
exogenous in nature). This differentiation
will, we hope, not only improve strategic
planning and decision-making but also
increase the utility of our report in private
and public sector institutions.
Our Special Report this year takes the first
steps towards developing a national
resilience measurement with regard to
global risks. It explores the use of qualitative
and quantitative indicators to assess overall
national resilience to global risks by looking
at five national-level subsystems
(economic, environmental, governance,
infrastructure and social) through the lens
of five components: robustness,
redundancy, resourcefulness, response
and recovery. The aim is to develop a new
diagnostic report to enable decisionmakers to track progress in building
national resilience and possibly identify
where further investments are needed. The
interim study will be published this summer.
Section 3
Resilience is the theme that runs through
the eighth edition of this report. It seems an
obvious one when contemplating the
external nature of global risks because they
are beyond any organization’s or nation’s
capacity to manage or mitigate on their
own. And yet global risks are often
diminished, or even ignored, in current
enterprise risk management. One reason
for this is that global risks do not fit neatly
into existing conceptual frameworks.
Fortunately, this is changing. The Harvard
Business Review recently published a
concise and practical taxonomy that may
also be used to consider global risks.1
There are three types of risks as categorized by Professors Kaplan and Mikes.
We have introduced unique content and
data online, including an interactive
website through which you can explore
the risks landscape and a one-year-on
follow-up of the three risk cases
presented in the 2012 report from a
perspective of how to promote resilience.
Section 2
Per the revamped methodology introduced in 2012, the 2013 report presents
three in-depth “risk cases” exploring
themes based on analysis of survey data,
as well as detailed follow-up expert
interviews and partner workshops. This
eighth edition increased its geographic
breadth and disciplinary depth by
bringing on two new report partners from
academia: the National University of
Singapore (NUS) and the Oxford Martin
School at the University of Oxford. We
also entered into an exciting editorial
partnership with Nature, a leading
science journal, to push the boundaries
of the imagination further with a revamped “X Factors” section of the report.
Section 1
Executive Summary
Section 2
Section 3
The World Economic Forum’s Global Risks
2013 report is developed from an annual
survey of over 1,000 experts from industry,
government, academia and civil society who
were asked to review a landscape of 50
global risks.
The global risk that respondents rated most likely to manifest
over the next 10 years is severe income disparity, while the risk
rated as having the highest impact if it were to manifest is major
systemic financial failure. There are also two risks appearing in
the top five of both impact and likelihood – chronic fiscal
imbalances and water supply crisis (see Figure 4).
Figure 4: Top Five Risks by Likelihood and Impact
Likelihood
Section 4
Very Unlikely
Almost Certain
4.14
3.99
3.91
Water supply crises
3.85
3.83
Section 5
1
2
3
4
5
Average Likelihood
Impact
High Impact
Low Impact
Section 6
4.05
Water supply crises
3.99
3.97
3.95
3.92
1
2
3
4
5
Average Impact
Unforeseen consequences of life science technologies was the
biggest mover among global risks when assessing likelihood,
while unforeseen negative consequences of regulation moved
the most on the impact scale when comparing the result with
last year’s (see Figure 5).
10
Global Risks 2013
Section 1
Figure 5: Top Five Changes by Likelihood and Impact
By Likelihood
Very Unlikely
of new life science technologies
3.11 [44th]
2013
2012
2.68 [49th]
3.23 [38th]
2.80 [46th]
3.45 [23rd]
3.05 [38th]
3.46 [21st]
3.07 [37th]
3.83 [5th]
3.44 [18th]
1
2
3
4
5
Average Likelihood Score [Rank]
Low Impact
Unforeseen negative
3.18 [43rd]
2013
2012
High Impact
2.77 [48th]
3.40 [30th]
3.02 [43rd]
3.73 [11th]
3.38 [27th]
3.66 [14th]
3.36 [28th]
2
3
4
5
Average Impact Score [Rank]
Three Risk Cases
Special Report: National Resilience to
Global Risks
This year’s Special Report examines the difficult issue of how a
country should prepare for a global risk that is seemingly beyond
its control or influence. One possible approach rests with
“systems thinking” and applying the concept of resilience to
countries. The report introduces five components of resilience
– robustness, redundancy, resourcefulness, response and
recovery – that can be applied to five country subsystems: the
economic, environmental, governance, infrastructure and social.
The result is a diagnostic tool for decision-makers to assess and
monitor national resilience to global risks.
Global Risks 2013
11
Section 6
Continued stress on the global economic system is positioned
to absorb the attention of leaders for the foreseeable future.
Meanwhile, the Earth’s environmental system is simultaneously
coming under increasing stress. Future simultaneous shocks to
both systems could trigger the “perfect global storm”, with
potentially insurmountable consequences. On the economic
front, global resilience is being tested by bold monetary and
austere fiscal policies. On the environmental front, the Earth’s
resilience is being tested by rising global temperatures and
extreme weather events that are likely to become more frequent
and severe. A sudden and massive collapse on one front is
certain to doom the other’s chance of developing an effective,
long-term solution. Given the likelihood of future financial crises
and natural catastrophes, are there ways to build resilience in
our economic and environmental systems at the same time?
Section 5
The report introduces three risk cases, based on an analysis of
survey results, consultation with experts and further research.
Each case represents an interesting constellation of global risks
and explores their impact at the global and national levels. The
three risk cases are:
Health is a critical system that is constantly being challenged, be
it by emerging pandemics or chronic illnesses. Scientific
discoveries and emerging technologies allow us to face such
challenges, but the medical successes of the past century may
also be creating a false sense of security. Arguably, one of the
most effective and common means to protect human life – the
use of antibacterial and antimicrobial compounds (antibiotics)
– may no longer be readily available in the near future. Every dose
of antibiotics creates selective evolutionary pressures, as some
bacteria survive to pass on the genetic mutations that enabled
them to do so. Until now, new antibiotics have been developed to
replace older, increasingly ineffective ones. However, human
innovation may no longer be outpacing bacterial mutation. None
of the new drugs currently in the development pipeline may be
effective against certain new mutations of killer bacteria that
could turn into a pandemic. Are there ways to stimulate the
development of new antibiotics as well as align incentives to
prevent their overuse, or are we in danger of returning to a
pre-antibiotic era in which a scratch could be potentially fatal?
Section 4
3.49 [27th]
3.15 [36th]
1
Section 3
By Impact
In 1938, thousands of Americans confused a radio adaptation of
the H.G. Wells novel The War of the Worlds with an official news
broadcast and panicked, in the belief that the United States had
been invaded by Martians. Is it possible that the Internet could
be the source of a comparable wave of panic, but with severe
geopolitical consequences? Social media allows information to
spread around the world at breakneck speed in an open system
where norms and rules are starting to emerge but have not yet
been defined. While the benefits of our hyperconnected
communication systems are undisputed, they could potentially
enable the viral spread of information that is either intentionally or
unintentionally misleading or provocative. Imagine a real-world
example of shouting “fire!” in a crowded theatre. In a virtual
equivalent, damage can be done by rapid spread of
misinformation even when correct information follows quickly.
Are there ways for generators and consumers of social media to
develop an ethos of responsibility and healthy scepticism to
mitigate the risk of digital wildfires?
Section 2
Almost Certain
Section 1
X Factors from Nature
Section 2
Section 3
Developed in partnership with the editors of Nature, a leading
science journal, the chapter on “X Factors” looks beyond the
landscape of 50 global risks to alert decision-makers to five
emerging game-changers:
- Runaway climate change: Is it possible that we have already
passed a point of no return and that Earth’s atmosphere is
tipping rapidly into an inhospitable state?
- Significant cognitive enhancement: Ethical dilemmas akin
to doping in sports could start to extend into daily working life;
an arms race in the neural “enhancement” of combat troops
could also ensue.
- Rogue deployment of geoengineering: Technology is now
being developed to manipulate the climate; a state or private
individual could use it unilaterally.
- Costs of living longer: Medical advances are prolonging life,
but long-term palliative care is expensive. Covering the costs
associated with old age could be a struggle.
- Discovery of alien life: Proof of life’s existence elsewhere in
the universe could have profound psychological implications
for human belief systems.
Section 4
The Global Risks report is the flagship research publication of
the World Economic Forum’s Risk Response Network, which
provides an independent platform for stakeholders to explore
ways to collaborate on building resilience to global risks. Further
information can be found at www.weforum.org/risk.
Section 5
Section 6
12
Global Risks 2013
Section 1
Box 1: The Evolving Risk Landscape
Section 2
How do the top risks as identified by the annual Global Risks Perception Survey change over time? Figure 6 shows how this list
changed over the past seven years. The average ratings of the risks have changed slightly, as described in detail in Section 4 of the
report, but the relative ranking of the risks according to their impact or their likelihood is less affected. Interestingly, the diffusion of
weapons of mass destruction has moved into the top five risks in terms of impact.iii
Figure 6: Top Five Global Risks in Terms of Impact and Likelihood, 2007-2013
Top 5 Global Risks in Terms of Likelihood
2008
2009
2010
Breakdown of
critical information
infrastructure
Asset price collapse
1st
2nd
Chronic disease
in developed
countries
Middle East
instability
Slowing Chinese
economy (<6%)
Oil price shock
Failed and failing
states
China economic
hard landing
2011
2012*
2013*
Meteorological
catastrophes
Severe income
disparity
Severe income
disparity
Slowing Chinese
economy (<6%)
Hydrological
catastrophes
Chronic fiscal
imbalances
Chronic fiscal
imbalances
Chronic disease
Chronic disease
Corruption
Rising greenhouse
gas emissions
Rising greenhouse
gas emissions
Oil and gas price
spike
Global governance
gaps
infrastructure
Fiscal crises
Biodiversity loss
Cyber attacks
Water supply crises
Chronic disease,
developed world
Retrenchment
from globalization
(emerging)
Global governance
gaps
Climatological
catastrophes
Water supply crises
Mismanagement
of population
ageing
2012*
2013*
Section 3
2007
Breakdown of critical information infrastructure
3rd
4th
Section 4
5th
Breakdown of
Top 5 Global Risks in Terms of Impact
2008
2009
2010
2nd
Retrenchment
from globalization
Retrenchment
from globalization
(developed)
Retrenchment
from globalization
(developed)
3rd
Interstate and
civil wars
Slowing Chinese
economy (<6%)
Pandemics
Oil price shock
2011
Fiscal crises
Major systemic
financial failure
Major systemic
financial failure
Retrenchment
from globalization
(developed)
Climatological
catastrophes
Water supply
crises
Water supply
crises
Oil and gas
price spike
Oil price spikes
Geopolitical
conflict
Food shortage
crises
Chronic fiscal
imbalances
Oil and gas
price spike
Chronic disease
infrastructure
Chronic disease
Chronic fiscal
imbalances
Food shortage
crises
Pandemics
Fiscal crises
Fiscal crises
Extreme energy
price volativity
Extreme volativity
in energy and
agriculture prices
Diffusion of
weapons of mass
destruction
1st
Section 5
2007
Breakdown of critical information infrastructure
Breakdown of
5th
Economic
Environmental
Geopolitical
Societal
Section 6
4th
Technological
iii
*The survey methodology changed significantly after the 2011 report. In contrast to the years 2007 to 2011, the list of 50 risks that was assessed by the survey did not change in 2012 and 2013.
Global Risks 2013
13
Section 1
Introduction
Section 2
Section 3
Section 4
The nature of global risks is constantly
changing. Thirty years ago, chlorofluorocarbons (CFCs) were seen as a planetary risk,
while threat from a massive cyber attack
was treated by many as science fiction. In
the same period, the proliferation of nuclear
weapons occupied the minds of scientists
and politicians, while the proliferation of
orbital debris did not. We see a similar story
with asbestos then and carbon nanotubes
today, and the list goes on.
Section 5
Section 6
With new information, the perceptions and
realities of risks change, and often in
unforeseen directions. Consider that in
some circles the threat from greenhouse
gas emissions made nuclear energy seem
less hazardous than fossil fuels over the long
run. Yet the nuclear catastrophe in
Fukushima, Japan, not only changed public
perceptions there but also energy policy,
almost overnight, in some parts of Europe.
The World Economic Forum is now in its eighth year of
publishing the Global Risks report. The purpose of the current
edition is twofold. First, it aims to show how experts from around
the world, from different backgrounds, currently perceive the
risks that the world is likely to face over the next decade. To
capture these opinions, a survey was carried out, interviews
were conducted with specialists in different fields, and a series
of workshops and conference sessions were held with expert
groups to interpret the research findings and to work out the
three risk cases developed in the report. Second, with this
report the World Economic Forum aims to continue to raise
awareness about global risks, to stimulate thinking about how
risks can be factored into strategy development, and to
challenge global leaders to improve how they approach global
risks.
Annual Survey – Assessing Global Risks
The Global Risks Perception Survey was conducted in
September 2012. Over 1,000 experts responded to evaluate 50
global risks from five categories – economic, environmental,
geopolitical, societal and technological. For each global risk,
survey respondents were asked, “On a scale from 1 to 5, how
likely is this risk to occur over the next 10 years?”, and “If it were
to occur, how big would you rate the impact of this risk?” The
aggregated responses to these two questions are depicted in
the Global Risks Landscape scatterplot in Figure 2.
The evaluation of the 50 risks also focused on their linkages,
given their interdependent nature. Survey respondents were
asked to nominate pairs of risks that they believe to be strongly
connected. They were also asked to nominate a “Centre of
Gravity” – the systemically most important risk for each of the
five categories of global risks. Putting all paired connections
together results in a network diagram presented in Figure 37 in
Section 4 – the Survey Findings.
The survey data was also analyzed to examine how the
background of the respondents affects their perceptions. Are
the views of people based in Europe similar to those in Asia? Do
younger people perceive the world differently from older people?
And how does specialist knowledge in a field affect how risks
are perceived? These questions are explored in Section 4 of this
report.
14
Global Risks 2013
Section 1
The Cases – Making Sense of Complex
Systems
Section 2
The 50 global risks in this report are interdependent and
correlated with each other. The permutations of two, three, four
or more risks are too many for the human mind to comprehend.
Therefore, an analysis of the network of connections has been
undertaken to highlight some interesting constellations of global
risks seen in Figure 3.
Section 3
In Section 2, these constellations of global risks are presented as
three important cases for leaders: “Testing Economic and
Environmental Resilience” on the challenges of responding to
climate change, “Digital Wildfires in a Hyperconnected World”
on misinformation spreading via the Internet, and “The Dangers
of Hubris on Human Health” on the existential threat posed by
antibiotic-resistant bacteria.
Section 4
Each case was inspired by the findings from an initial network
analysis and further developed through extensive research into
current trends, potential causal effects, levels of awareness and
possible solutions. Unlike traditional scenario methodologies,
the risk cases do not attempt to develop a full range of all
possible outcomes. They are instead an exercise in sensemaking as well as a collective attempt to develop a compelling
narrative around risks that warrant urgent attention and action
by global leaders. Readers are encouraged to refine these cases
further and to develop their own scenarios based on the data
presented.iv
X Factors from Nature – Looking Even
Further Ahead
Section 5
The section on X Factors invites the reader to consider emerging
concerns that are not yet on the radar of decision-makers. If the
50 global risks represent “known-knowns”, then these X factors
could be considered as “known unknowns”. They were codeveloped with the editors of Nature and benefit from their
contributors’ deep knowledge of cutting-edge scientific research that has not yet crossed over into mainstream discourse.
Resilience – Preparing for Future Shocks
iv
v
Section 6
This year’s Special Report examines the increasingly important
issue of building national resilience to global risks. It introduces
qualitative and quantitative indicators to assess overall national
resilience to global risks by looking at five national-level
subsystems (economic, environmental, governance,
infrastructure and social) through the lens of five components:
robustness, redundancy, resourcefulness, response and
recovery. The aim is to develop a future diagnostic report to
enable decision-makers to track progress in building national
resilience and possibly identify where further investments are
needed. The interim study will be published this summer, and
we invite readers to review the proposed framework and to
share ideas and suggestions with the Risk Response Network.v
See also the World Economic Forum’s series of “What-If” interviews for more case studies
on a variety of topics: http://forumblog.org/tag/what-if/.
For further details please refer to http://www.weforum.org/risk or contact us at rrn@
weforum.org.
Global Risks 2013
15
Section 1
Section 2
Testing Economic and
Environmental Resilience
Section 3
Section 4
Section 5
Economic and environmental systems are
simultaneously under stress worldwide, and
this is testing resilience at the global and
national levels. Economic difficulties
worldwide are continuing to make greater
demands on political attention and financial
resources. Meanwhile, the impact of climate
change is more evident as temperature rises
and more frequent extreme weather events
loom on the horizon. The economic and
environmental challenges require both
structural changes and strategic investments,
but are countries prepared to manage both
fronts, conceivably at the same time?
Five years after the financial crisis, macroeconomic worries
continue to weigh heavily on leaders’ minds. This is confirmed
by data from the World Economic Forum’s quarterly confidence
indexvi as well as the Global Risks Perception Survey, in which
respondents rated major systemic financial failure as the
economic risk of greatest systemic importance for the next 10
years.
The very same survey respondents also identified the failure of
climate change adaptation and rising greenhouse gas emissions
as among those global risks considered to be the most likely to
materialize within a decade. Compared to last year’s survey, the
failure to adapt to climate change replaced rising greenhouse
gas emissions as the most systemically critical. This change in
our data mirrors a wider shift in the conversation on the
environment from the question of whether our climate is
changing to the questions of “by how much” and “how quickly”.
Figure 7: Testing Economic and Environmental Resilience Constellation
Major systemic financial failure
Section 6
Global
governance
failure
Water supply crises
Persistent extreme weather
Chronic fiscal
imbalances
The Environmental System
The Economic System
16
Global Risks 2013
vi
The Global Confidence Index is an index developed by the World Economic Forum that
represents confidence among decision-makers in three areas: global economy, global
governance and global cooperation. For greater detail, please consult: http://www.
weforum.org/ConfidenceIndex
Section 1
The narrative emerging from the survey is clear: like a super
storm, two major systems are on a collision course. The
resulting interplay between stresses on the economic and
environmental systems will present unprecedented challenges
to global and national resilience.
Philippines
Thailand
Mexico
Argentina
Kenya
Malaysia
Morocco
Pakistan
Brazil
India
Jordan
Section 2
Germany
United Kingdom
France
Belgium
Iceland
United States
Ireland
Portugal
Italy
Japan
Greece
Section 3
Will countries be able to address complex challenges unfolding
on very different time scales simultaneously? A cynic may argue
that any future environmental loss could actually have a
stimulative economic effect – this is the same rationale used to
criticise GDP-driven growth policies, whereby the reconstruction
following a massive earthquake can boost overall GDP over the
long term. However, this view ignores two realities. First, more
people reside and work in urban areas than ever before in
human history – this concentration will continue and is likely to
drive environment-related losses to even greater historic highs.
Second, the existing debt levels of many major economies can
be unsustainable. Given this fiscal constraint, we are witnessing
the use of extraordinary monetary policies to stimulate global
growth, which some argue are essentially experimental.
Figure 8: Further Required Deficit Reductions for Fiscal
Sustainability (2011)
0
100
150
200
-5
0
5
10
15
20
Required adjustment (% GDP)
Source: Adapted from IMF Fiscal Monitor, 2012 as cited in Global Economic Prospects: Managing
Growth in a Volatile World. June, 2012. Washington DC: World Bank.
The current eurozone instability will continue to shape global
prospects in the coming years.5 The associated risk of systemic
financial failure, although limited, cannot be completely
discarded. Given the anti-austerity protests across the eurozone,
the election of “rejectionist” governments could lead to further
economic paralysis and bring the eurozone crisis to a head,6
potentially destabilizing the global financial system in which
confidence is already waning.7
This persistent global economic fragility continues to divert our
attention from longer-term solutions by limiting the availability of
public resources and generating greater caution in use of scarce
funds for strategic investment projects. There are other looming
issues related to ongoing prescriptions to counter economic
malaise. Will the massive quantitative easing undertaken by key
central banks to stave off deflation inevitably lead to destabilizing
hyper-inflation? Will structural economic reforms deliver the
necessary employment gains over the long run?
Section 6
The global economic situation remains fragile. The International
Monetary Fund projects slow growth in the advanced
economies, an annual rate of between 1.3% and 2.6% between
2012 and 2017.2 Combined with fiscal fragility, this will continue
to strain government spending. Given the current levels of
government debts and deficits in these economies, “it will take
years of concerted political and economic effort before debt to
GDP levels of the United States, Japan and many Euro Area
countries are brought down” to stabilize at lower levels.3 Also,
the economic growth of emerging markets and developing
economies is projected to be slower than at its peak in 2010.4
Section 5
Persistent Global Economic Fragility
50
Gross debt (% of GDP)
Section 4
The fact remains that today’s massive socio-economic
challenges demand immediate attention, yet availability of public
resources is limited – especially to finance efforts to avert the
long-term effects of climate change, which, in turn, could
severely disrupt the global economy. We face a daunting
negative feedback loop. The logic of risk management
prescribes that countries should invest today to safeguard
critical infrastructure and centres of economic activity against
future climate-related losses that could be of much greater
magnitude. And there is an even more compelling political logic
to do this in order to generate new employment and to revive
economic growth as soon as possible. But investment in
strategic infrastructure is more easily said than done, despite the
short- and long-term benefits.1 New approaches are needed
that are based on a meeting of minds across varied professions,
sectors and geographies; a capacity to act decisively is also
needed, despite considerable uncertainty about what the best
plan of action might be. Hesitating to act now will only add to the
burdens of the next generation.
Global Risks 2013
17
Section 1
The Changing Debate on the Global
Climate
Section 2
Section 3
Mitigation efforts have made significant progress at country level
in the past 15 years in areas such as emissions regulations and
financial incentives – for example, the US$ 3.4 billion made
available to match private sector investment funds in the US
Smart Grid Investment Grant program.8 Nonetheless, in today’s
increasingly multi-polar geopolitics, it has become harder to
reach and effectively implement international agreements on
climate change mitigation. Pledges made in the run-up to the
2009 Copenhagen climate change negotiations, which were
intended to limit global warming to 2 degrees Celsius, now
appear collectively insufficient to meet this target of 2 degrees.9
Recent scenario projections based on existing government
policies and declared policy intentions predict that a long-term
increase of more than 3.5 degrees Celsius is probable. The
more pessimistic scenario assuming no change in government
policies and measures beyond those adopted or enacted by
mid-2011 talks of a conceivable increase of 6 degrees Celsius or
more.10
Section 4
If the current mitigation commitments remain unmet, a global
mean temperature increase of 4 degrees Celsius could occur as
early as the 2060s. This would likely lead to negative impacts
including an increase in the frequency of high-intensity tropical
cyclones, inundation of coastal cities as sea levels rise, and
increased drought severity in several regions. Together, the
effects would not only mean significant economic losses but
also mass displacement of populations, rising food insecurity
and aggravated water scarcity11 (also see Figure 9).
Recent climate and weather events, some of which are
visualized in Figure 10, have reminded us of the economic and
human cost of the kind of natural disasters that we know are
likely to become more frequent and severe as climate continues
to change. The estimated economic cost of the 2011 Thailand
floods, for example, was US$ 15 billion to US$ 20 billion,12 and of
Hurricane Katrina US$ 125 billion; meanwhile, the 2003
European heat wave resulted in more than 35,000 fatalities13 and
the Horn of Africa droughts in 2011 claimed tens of thousands of
lives and threatened the livelihoods of 9.5 million people.14 More
recently, Hurricane Sandy left a heavy bill, estimated today at
over US$ 70 billion for New York and New Jersey alone.15 Such
events remind us that many economies remain vulnerable to
damages arising from climatic events today, let alone those of
the future.16
While there is no consensus on how fast and how much our
climate is changing, the growing realization that some degree of
climate change is inevitable is reflected in a shifting of the debate
to how to adapt. Advocating for greater attention to be paid to
adaptation is controversial in some quarters as it is interpreted
as a tacit admission that mitigation efforts are no longer worth
pursuing. However, the less effective mitigation efforts are, the
more pronounced adaptation challenges will become; therefore,
mitigation and adaptation need to be addressed in concert while
taking advantage of all possible synergies.
Figure 9: Possible Impact of Global Warming on Different Sectors
Temperature above preindustrial - IPCC scenario A1B
Section 5
Year of impact:
2030
2050
1°C
2°C
Weather
Water
2080
3°C
4°C
5°C
More intense storms, forest fires, droughts, flooding and heat waves
Threat to local water
supply as glaciers melt
Section 6
Food
Ecosystem
Social
Changes in water availability, threatening up to a billion
people
Falling crop yields in many developing regions
Ecosystems extensively
and irreversibly damaged
Major cities around the world
threatened by sea level rise
Falling yields in many developed regions
Many more species
face extinction
More than a billion people may have to migrate - increasing the risk of conflicts
Source: Adapted from Shaping Climate-Resilient Development: A Framework for Decision-Making. 2009. Economics of Climate Adaptation Working Group.
18
Global Risks 2013
Section 1
Figure 10: 2011 Economic Losses Related to Selected Natural Catastrophes
Section 2
>US$25,000m
Section 3
US$5,000m - US$25,000m
US$1,000m - US$5,000m
US$250m - US$1,000m
US$100m - US$250m
US$50m - US$100m
< US$50m
Earthquake, Tsunami, Volcano
Extreme Weather
Flood
Section 4
Storm, Hail
Source: Adapted from sigma natural catastrophe data base of Swiss Reinsurance Company.
A number of climate adaptation related initiatives and reports
have been emerging.vii While poorer countries will need help
from the international community to finance adaptation
investments, adaptation efforts are by their nature local, with
countries, companies and individuals being largely responsible
for their own adaptation costs.
vii
For examples please see “Shaping Climate-Resilient Development: A Framework for
Decision-Making” by the Economics of Climate Adaptation Working Group, “Managing the
Risks of Extreme Events and Disasters to Advance Climate Change Adaptation” Special
Report of the Intergovernmental Panel on Climate Change, and Private Sector Initiative of
the UNFCCC’s Nairobi Work Programme featuring good practices and climate change
adaptation activities undertaken by the private sector (some of which have been carried
out in partnership with NGOs or the public sector) across different regions and sectors.39
Faced with uncertainty about the likely effectiveness and risk
of unintended consequences of a proposed intervention,
policy-makers can be paralyzed by a desire to wait for more
detailed analyses and data regarding the precise timing,
manifestation or impact of future climatic changes in their local
environments. Greater support for scientific research, better
computational power and data are needed to shed greater
clarity into predicting future climatic developments, especially
the climate and weather extremes.
Global Risks 2013
19
Section 6
Some people affected by climate change may seek to recover
costs from past emitters of greenhouse gases. Although the
Alaskan village of Kivalina – which faces being “wiped out” by
the changing climate – was unsuccessful in its attempts to file a
US$ 400 million lawsuit against oil and coal companies,20,21
future plaintiffs may be more successful. Five decades ago, the
US tobacco industry would not have suspected that in 1997 it
would agree to pay US$ 368 billion in health-related damages.22
For some businesses, investing in climate change mitigation
now could be as much about enterprise risk management as
about mitigating a global risk.
As the consensus that the climate change is becoming more
evident grows, data across many disciplines (including
forestry, water and land management, for example) remains
limited, not readily available or communicated in a format that
might not facilitate actionable decisions on climate adaptation.
Yet, future climate risks may require human judgement today
or in the coming years, while the full scientific data may not
come until it is too late. Complex systems such as the climate
are non-linear by nature – chain reactions through the system
are unpredictable and not directly proportional to the size of
the triggers. A limited amount of data and constraints on
computational power have been strong impediments to
bringing greater clarity into predicting future climatic
developments at a local level.23,24 For instance, there have
been inconclusive predictions regarding the likely impacts of
global warming on rainfall patterns in Guyana: possibilities
ranged from a 5% rainfall decline by 2030, lessening the risk of
flooding, to a 10% rainfall increase, worsening this risk
significantly.25
Section 5
While it is possible to make various different underlying
assumptions in modelling the effects of climate change, it is
clear that the economic costs are likely to be considerable. A
report by Mercer,17 which considers the cumulative economic
cost of changes to the physical environment, health and food
security due to climate change, quotes a possible range of US$
2 trillion to US$ 4 trillion by 2030 across different climate
scenarios.18 The EU Climate Change Expert Group suggests
that the costs of climate change impacts, increasing in
magnitude with the rises in global temperature, may amount to
5% to 20% of GDP (or higher) in the long term.19
Decisive Action in a Climate of
Uncertainty
Section 1
Section 2
Section 3
While this will come, can leaders embrace the need to make a
decision without the complete assurance that they are making
the best decision? This is more easily said than done, especially
when there are competing demands for attention and
resources. For example, the 2008 financial crisis shows how
urgent macroeconomic difficulties can divert attention from
other significant global governance challenges, from climate
change negotiations to the Millennium Development Goals. Yet
the actions of the G20 during the crisis also demonstrate the
potential for bold, coordinated international action.
Exploring New Approaches with
Climate-Smart Mindsets
As global risks ultimately require a national response, much
more attention must be given to how decisions are made in the
face of such overwhelming economic and environmental
challenges. Perception is typically regarded as a passive
process, in which people view an objective reality. Yet
perception is actually an active process of understanding,
through which people construct their own version of reality.26
Research in cognitive psychology and decision-making
suggests that people use “rules of thumb” to make judgements
in the face of ambiguity and complexity.viii This approach usually
serves well but can lead to predictably faulty judgements under
some circumstances. Psychologists call such predictably faulty
judgements cognitive biases,27 and these biases influence how
we respond to the best information at our disposal and
integrate it in decision-making structures.
To reconcile the challenge of building environmental resilience
amid economic stress, current policies and strategies may
need to be re-evaluated. For instance, in several countries,
government insurance schemes and building-permit policies
continue to encourage further urbanization in coastal or high
flood risk areas rather than preventing it.33 In doing so, they may
be creating large pockets of vulnerability to climate risks. A
2007 OECD study analysing 136 port cities around the world
concluded that the population exposed to coastal flooding
could triple by the 2070s due to the combined effects of climate
change and urbanization, among others.34
Section 4
Section 5
Section 6
Cognitive biases become important when addressing the
slow-moving future threat of climate change in the context of
an ongoing unstable economic outlook. Some examples are:
- We tend to place too much emphasis on recent personal
experience when estimating the likelihood of a risk
occurring. For example, experience in the United States
shows that many more people buy flood insurance
immediately after a major flood. On average, those people
hold flood insurance for only two to four years before letting
it lapse if they have not suffered a claim because they are
likely to view insurance as a bad investment rather than
seeing it as a form of protection.28
- Through a process known as hyperbolic discounting, we
tend to give disproportionately more weight to immediate
costs and benefits than to delayed ones. Individuals, for
instance, may often be reluctant to incur the upfront costs
of measures such as investing in climate change adaptation
measures when the benefits will not be felt for several
years.29,30
- We fail to take protective measures if the perceived
likelihood of the risk in question is below our threshold level
of concern – for example, discounting entirely the possibility
of a natural catastrophe that has a low chance of occurring.
This bias is exacerbated by a tendency to underestimate
the likelihood of a negative event occurring due to
misperceptions of the risk.31,32
The cumulative effect of such cognitive biases is that we may
not pay due attention to, or act effectively on, risks that are
perceived to be long-term and relatively uncertain. The
impossibility of fully eradicating ambiguity, along with the
relatively lengthy time scales involved, mean that cognitive
biases are likely to remain significant hurdles to be
acknowledged and overcome on the path towards effective
action on climate change and related risks.
viii
20
The phrase “rule of thumb” means a quick and easy way of making estimates, based on
experience that will not be precisely accurate but will nonetheless be adequate for most
everyday situations.
Global Risks 2013
Acknowledging the effect of our cognitive biases may be the
first step towards building resilience against a future perfect
storm of economic and environmental challenges. Only then
can we start weighing the various demands equally, in the near
and the long term, on scarce public resources and dwindling
risk-mitigation budgets.
In light of the increased certainty that global temperatures will
rise to some extent, a “climate-smart” mindset needs to
permeate all levels of decision-making. “Climate-smart” is a
term that originated in agriculture, to describe such agriculture
that not only increases resilience in light of climate adaptation
but also reduces greenhouse gas emissions.35 A climate-smart
mindset incorporates climate change analysis into strategic and
operational decision-making. It entails a search for synergies
across climate change mitigation- and adaptation-related
efforts where possible. Such a mindset needs to become an
integral part of our urban planning, water- and food-security
management, investment policy, and demographic policy
development, among others. In 2006, during its term over the
rotating European Union presidency, Finland introduced a
policy innovation which encouraged ministers with other
portfolios – from transport and urban planning, to agricultural
and employment policies – to consider the effects of their
decisions on the population’s health.36 Something similar may
be needed to ensure that all ministers enact policies in their
domains that are informed by a climate-smart mindset.
The current debt crisis of several leading economies will make it
more difficult to finance climate-smart activities, such as the Smart
Grid Investment Grant. That said, the private sector has a critical
role here as well. In the United States, around 80% of critical
infrastructure is owned or operated by the private sector, not
governments.37 It is likely that many of the preparations to weather
the colliding economic and environmental storm systems will be
found in private-sector initiatives to reinforce critical assets and
shield them from potential future risks and liability.
Given the pressure on public finances generally and their
scarcity to address climate change-related challenges, new
funding models will need to be found. Private funds can be
unlocked through innovative public-private collaboration that
ranges across disciplines as well as stakeholders. In order to
enable scalable, effective partnerships, a variety of actors and
professional disciplines will need to converge on mutually
beneficial and economically sustainable solutions. This is no
minor task since, in addition to the diversity of interests at stake,
different professionals often have conflicting biases and have
been trained to think in siloed ways. Yet such partnerships have
started to emerge.
Section 1
Questions for Stakeholders
The World Economic Forum is serving as the secretariat for the
G2A2.
Global Risks 2013
21
Section 6
1. Highlight innovative models for public-private
collaboration: The G2A2 will launch a report at the 2013
World Economic Forum Annual Meeting identifying existing
sources of finance and pinpointing innovative ways for public
policy to unlock private funds.
2. Stimulate private investment at country level: The G2A2 is
working with the governments of Kenya, Vietnam and Mexico
to incubate innovative financing models with the domestic
and international private sector.
3. Provide new ideas and models to shape the policy
agenda: The G2A2 has formed working groups on green
free trade, end-user financing of renewable energy,
institutional investors and energy efficiency. The energy
efficiency working group is looking to pilot new financing
structures for energy services companies; the green freetrade group has led calls to establish free-trade regulations for
clean technologies such as solar.
4. Help to scale up and replicate successful approaches: To
help governments, development banks and finance
institutions to ensure rapid replication and to scale up
successful models, the G2A2 will document case studies in
the Green Investment Report and engage with policy
platforms and investor networks, such as the G20
Development Working Group and Finance Track group on
climate finance, the UNFCCC’s Momentum for Change
Initiative and the International Development Finance Club. The
G2A2 will also collaborate closely with the UN Sustainable
Energy for All Initiative and the Global Investor Coalition on
Climate Change.
Section 5
- How will we reconcile climate change mitigation and
adaptation efforts with the desire for prosperity given current
demographic trends?
- How can like-minded municipalities, companies and
communities drive forward a new set of climate-smart
approaches that avoid cognitive biases?
- How can we rethink cross-industry collaboration to find the
right balance between competition and cooperation among
companies in a resource-constrained and increasingly
interconnected world?
To address the current shortfall in green infrastructure
investment, more than 50 leading companies from finance,
infrastructure, energy and agriculture sectors joined with public
finance institutions to launch the Green Growth Action Alliance
(G2A2) at the 2012 G20 Summit in Mexico. Chaired by the then
Mexican President Felipe Calderón, the G2A2 will pursue four
strategic activities over a two-year timeframe:
Section 4
As the world faces a squeeze in public funds at the same time
as the effects of climate change are increasing, it is only through
collaboration among governments (to further the public
interest), businesses (to search for innovative products and
solutions), legal experts (to mitigate fear of liability), science (to
bring good quality supporting data and analyses) and the
financial sector (to innovate and avoid future damaging costs)
that the limits of environmental and economic resilience can be
successfully navigated.
As emerging economies grapple with how to grow their
economies without worsening their environments, many are
developing “green growth” strategies designed to attract
investment in sustainable water, energy, transport and
agricultural infrastructure. Up to US$1 trillion a year of private
sector investment is needed, according to the 2012 B20 Green
Growth Task Force. However, due to the limited track record of
some technologies, combined with the perception of investment
risk, private capital providers are often reluctant to invest in
green growth.
Section 3
Other examples of innovative partnerships include a company in
China which has partnered with government, industry
associations and international NGOs to enable a sector-wide
replication of green prefabrication production, currently saving
360 hectares of forest and 314,000 tons of greenhouse gas
emissions a year; and the Desertec Foundation for Clean Energy
Generation, which assisted in founding an industrial initiative of
55 industrial and financial companies and institutions working to
enable large-scale generation of renewable power from deserts
to serve markets in North Africa, Middle East and Europe.38
Box 2: The Green Growth Action Alliance
(G2A2)
Section 2
In order to address the current shortfall in green infrastructure in
a number of emerging economies, more than 50 leading
companies from finance, infrastructure, energy and agriculture
sectors joined public institutions to form the Green Growth
Action Alliance (G2A2). As described in greater detail in Box 2,
the aim of this initiative is to unlock greater sums of private
investment for green infrastructure.
Section 1
References
Section 2
Section 3
Section 4
Section 5
Section 6
1.
Strategic Infrastructure Steps to Prioritize and Deliver Infrastructure Effectively and Efficiently.
September, 2012. Geneva: World Economic Forum in collaboration with PwC.
2.
World Economic Outlook: Coping with High Debt and Sluggish Growth. October, 2012.
Washington DC: International Monetary Fund.
3.
Global Economic Prospects: Managing Growth in a Volatile World. June, 2012. Washington DC:
World Bank.
4.
World Economic Outlook: Coping with High Debt and Sluggish Growth. October, 2012.
Washington DC: International Monetary Fund.
5.
Global Economic Prospects: Managing Growth in a Volatile World. June, 2012. Washington DC:
World Bank.
6.
Eichengreen, B. “Europe’s Populists at the Gate”. Project Syndicate, A World of Ideas, http://
www.project-syndicate.org/commentary/the-political-risk-to-the-euro-by-barry-eichengreen,
2012.
7.
Tonkin, S. “Global Experts Poll: Economic Confidence Plummets to Lowest Level in Five
Quarters”. World Economic Forum, http://www.weforum.org/nr_gci5.
8.
Smart Grid Investment Grant Program, Progress Report. July, 2012. U.S. Department of Energy,
Electricity Delivery and Energy Reliability.
9.
Too Late for Two Degrees? Law Carbon Economy Index 2012. November, 2012.
PricewaterhouseCoopers LLP.
10.
World Energy Outlook 2011. 2011. Paris: International Energy Agency.
11.
Turn Down the Heat. Why 4 C Warmer World Must Be Avoided. A Report for the World Bank by
the Potsdam Institute for Climate Impact Research and Climate Analytics. November, 2012.
Washington DC: World Bank.
12.
Garside, J. “Thailand Flooding Costs Lloyd’s of London $2.2bn”. The Guardian, http://www.
guardian.co.uk/business/2012/feb/14/lloyds-thailand-flooding-2bn-dollars, 2012.
13.
Shaping Climate-Resilient Development: A Framework for Decision-Making. 2009. Economics
of Climate Adaptation Working Group.
14.
Tavanti, M. “From Food Insecurity to Food Security: Understanding Human and Food Security
Implications for Somalia and the Horn of Africa”. Somalia Strategy Review, http://www.
somaliastrategyforum.org/journal/v1i1/tavanti_foodsecurity_v1i1.pdf, 2012.
15.
“Hurricane Sandy’s Rising Costs.” The New York Times, http://www.nytimes.com/2012/11/28/
opinion/hurricane-sandys-rising-costs.html, 2012.
16.
17.
Climate Change Scenarios–Implications for Strategic Asset Allocation. 2011. Mercer.
18.
Ibid.
19.
The 2°C Target. Background on Impacts, Emission Pathways, Mitigation Options and Costs.
July, 2008. EU Climate Change Expert Group.
20.
Lean, G. “Micronesia Lawsuit Highlights Climate Change Litigation”. The Telegraph, http://www.
telegraph.co.uk/earth/environment/climatechange/8533367/Micronesia-lawsuit-highlightsclimate-change-litigation.html, 2011.
21.
Saxe, D, James, M. “Kivalina Loses its Climate Change Nuisance Case Again”. http://envirolaw.
com/kivalina-loses-climate-change-appeal/, 2012.
22.
Gruber, J. “The Economics Of Tobacco Regulation”. Health Affairs, http://content.healthaffairs.
org/content/21/2/146.full, 2011.
23.
Based on comments from expert review.
24.
Palmer, T. A CERN for Climate Change. In Physics World, 2011, 24:14-15.
25.
26.
Heuer, R.J. Psychology of Intelligence Analysis. Center for the Study of Intelligence, Central
Intelligence Agency, 1999. https://www.cia.gov/library/center-for-the-study-of-intelligence/
csi-publications/books-and-monographs/psychology-of-intelligence-analysis/PsychofIntelNew.
pdf
27.
Ibid.
28.
Michel Kerjan, E., Lemoyne de Forges, S. and Kunreuther, H. Policy Tenure Under the US
National Flood Insurance Program (NFIP). In Risk Analysis, 2011, 32(4):644-658.
29.
Michel-Kerjan, E. Overcoming Decision Biases to Reduce Lossesfrom Natural Catastrophes. In
E. Shafir (ed), Behavioural Foundations of Policy. 2012. Princeton: Princeton University Press
30.
Laibson, D. Golden Eggs and Hyperbolic Discounting. In The Quarterly Journal of Economics,
1997, 112(2):443-478.
31.
32.
Kunreuther H., Meyer, R. and Michel-Kerjan, E. Overcoming Decision Biases to Reduce Losses
from Natural Catastrophes.Behavioural Foundations of Policy. In E. Shafir (ed), 2012. Princeton:
Princeton University Press.
33.
34.
Nicholls, R.J., Hanson, S. and Herweijer, C. et al. Ranking of the World’s Cities Most Exposed to
Coastal Flooding Today and in the Future, Executive Summary. 2007. Organisation for Economic
Co-operation and Development.
35.
“Climate-Smart” Agriculture: Policies, Practices and Financing for Food Security, Adaptation
and Mitigation. 2010. Rome: Food and Agriculture Organization of the United Nations.
36.
Puska, P. Health in All Policies. In The European Journal of Public Health, 2007, 17(4):328.
37.
Report of the Critical Infrastructure Task Force. January, 2006. Homeland Security Advisory
Council, http://www.dhs.gov/xlibrary/assets/HSAC_CITF_Report_v2.pdf
38.
Annex to the Message from the Friends of Rio+20. 2012. The Friends of Rio+20. http://www3.
weforum.org/docs/WEF_FriendsRio20_Annex_2012.pdf
39.
“Private Sector Initiative - Database of Actions on Adaptation”. United Nations Framework
Convention on Climate Change, http://unfccc.int/adaptation/nairobi_work_programme/
private_sector_initiative/items/6547.php, 2012.
22
Global Risks 2013
Section 1
In 1938, when radio had become widespread, thousands of Americans
confused an adaptation of the H.G. Wells novel War of the Worlds with a
news broadcast and jammed police station phone lines in the panicked
belief that the United States had been invaded by Martians.
Section 5
The Internet remains an uncharted, fast-evolving territory. Current
generations are able to communicate and share information
instantaneously and at a scale larger than ever before. Social media
increasingly allows information to spread around the world at
breakneck speed. While the benefits of this are obvious and well
documented, our hyperconnected world could also enable the rapid
viral spread of information that is either intentionally or unintentionally
misleading or provocative, with serious consequences. The chances
of this happening are exponentially greater today than when the
radio was introduced as a disruptive technology, despite our media
sophistication. Radio was a communication channel of “one to
many” while the Internet is that of “many to many”.
Section 4
It is difficult to imagine a radio broadcast causing comparably
widespread misunderstanding today. In part this is because
broadcasters have learned to be more cautious and responsible,
in part because the media is a regulated industry, and in part
because listeners have learned to be more savvy and sceptical.
Moreover, the news industry itself is undergoing a transformation as
the Internet offers multiple options to confirm or refute a breaking news
story. But the Internet, like radio in 1938, is a relatively young
medium. The notion that a tweet, blog or video posting could drive a
similar public panic today is not at all far-fetched.
Section 3
The global risk of massive digital
misinformation sits at the centre of a
constellation of technological and
geopolitical risks ranging from terrorism to
cyber attacks and the failure of global
governance. This risk case examines how
hyperconnectivity could enable “digital
wildfires” to wreak havoc in the real world. It
considers the challenge presented by the
misuse of an open and easily accessible
system and the greater danger of misguided
attempts to prevent such outcomes.
Section 2
Digital Wildfires in a
Hyperconnected World
Figure 11: Digital Wildfires in a Hyperconnected World Constellation
Section 6
Cyber attacks
Terrorism
Failure of diplomatic conflict resolution
Major
Major
systemic
systemicfinancial
financial failure
failure
Global Risks 2013
23
Section 1
Section 3
US Internet users who use social networks sites, by age,
in percentage of each group
18-29 years
30-49 years
50-64 years
65+ years
80
73%
83%
86%
58%
61%
76%
67%
60
48%
25%
16%
12%
7%
5%
22%
11%
4%
13%
Apr 2009
0
25%
16%
Nov 2008
20
47%
36%
36%
7%
Dec 2009
40
26%
May 2010
100
May 2008
How might digital wildfires be prevented? Legal restrictions on
online anonymity and freedom of speech are a possible route,
but one which may also have undesirable consequences. And
what if the source of a digital wildfire is a nation state or an
international institution? Ultimately, generators and consumers of
social media will need to evolve an ethos of responsibility and
healthy scepticism similar to that which evolved among radio
broadcasters and listeners since the infamous War of the Worlds
broadcast in 1938. This risk case asks if explicitly recognizing
the potential problem and drawing attention to possible solutions
could facilitate and expedite the evolution of such an ethos.
Figure 13: Users Timeline
Sep 2005
Section 2
The Internet does have self-correcting mechanisms, as Wikipedia
demonstrates. While anyone can upload false information, a
community of Wikipedia volunteers usually finds and corrects errors
speedily. The short-lived existence of false information on its site is
generally unlikely to result in severe real-world consequences;
however, it is conceivable that a false rumour spreading virally
through social networks could have a devastating impact before
being effectively corrected. It is just as conceivable that the offending
content’s original author might not even be aware of its misuse or
misrepresentation by others on the Internet, or that it was triggered
by an error in translation from one language to another. We can think
of such a scenario as an example of a digital wildfire.
Source: Adapted from “Search Engine Journal”, http://www.searchenginejournal.com/
wp-content/uploads/2011/09/social-media-black.jpeg, 2012.
Benefits and Risks of Social Media
Section 4
From cuneiform to the printing press, it has always been hard to
predict the ways in which new communication technologies will
shape society. The scale and speed of information creation and
transfer in today’s hyperconnected world are, however, historically
unparalleled. Facebook has reached more than 1 billion active
users in less than a decade of existence, while Twitter has
attracted over 500 million active users in seven years. Sina-Weibo,
China’s dominant micro-blogging platform, passed 400 million
active accounts in summer 2012.1 Every minute, 48 hours’ worth of
content is uploaded to YouTube. The world of social media is
multicultural and young. Figures 12 and 13 show the preferences
across the world for different social networking platforms, and the
trends of social media use by age group in the United States.
Figure 12: The World of Social Media
Section 5
Leading social media networks by country
Russia
VKontakte
Odnoklassniki
Facebook
Section 6
USA
Facebook
Twitter
Linkedin
Dominating networks
by country
UK
Facebook
Twitter
Linkedin
China
Qzone
Sina Weibo
Renren
Egypt
Facebook
Twitter
Facebook
Qzone
VKontakte
Odnoklassniki
Orkut
Mixi
Zing
Cloob
Draugiem
Brasil
Orkut
Facebook
Twitter
India
Facebook
Orkut
Twitter
South Africa
Facebook
Twitter
Linkedin
Australia
Facebook
Twitter
Linkedin
No data
Source: Adapted from “Search Engine Journal”, http://www.searchenginejournal.com/wp-content/uploads/2011/09/social-media-black.jpeg, 2012.
24
Global Risks 2013
Japan
Mixi
Twitter
Facebook
Section 1
These cases indicate one of the two situations in which digital
wildfires are most dangerous: in situations of high tension, when
false information or inaccurately presented imagery can cause
damage before it is possible to propagate accurate information.
The real-world equivalent is shouting “fire!” in a crowded theatre
– even if it takes only a minute or two for realization to spread
that there is no fire, in that time people may already have been
crushed to death in a scramble for the exit.
Executives interviewed by Forbes and Deloitte placed social
media among the greatest risks that their corporations face.23
For example, after the BP oil spill in the Gulf of Mexico, a parody
Twitter account quoting the chief executive Tony Hayward as
saying such things as “Black sand beaches are very trendy in
some places” attracted 12 times more followers than BP’s
corporate Twitter account.24 While this example might have been
intended to be humorous, it is possible for satire to be mistaken
for fact. In October 2012, Iran’s official news agency ran a story
that originated on the satirical website The Onion, claiming that
opinion polls showed Mahmoud Ahmadinejad was more
popular than Barack Obama among rural white Americans.25
Global Risks 2013
25
Section 6
As Hurricane Sandy battered New York in October 2012, an
anonymous Twitter user tweeted that the New York Stock
Exchange trading floor was flooded by three feet of water. Other
Twitter users quickly corrected the false rumour, though not
before it was reported on CNN.13 In Mexico, there have been
cases of mothers needlessly keeping their children from school
and shops closing due to false rumours of shootouts spreading
through social networks.14 In the UK, the video imagery related
to a low level tactical incident of the British Army in Basra,
spread through Reuters agency feed, YouTube and Blinkx, led to
a misleading impression of a significant military failure among the
British public which was never fully eradicated.15
While it is certainly possible for a digital wildfire to start
accidentally, it is also possible for misinformation to be
deliberately propagated by those who stand to reap some kind
of benefit. Some examples:
- In politics, the practice of creating the false impression of a
grassroots movement reaching a group consensus on an
issue is called “astroturfing”. During the 2009 Massachusetts
special election for the US Senate, a network of fake Twitter
accounts successfully spread links to a website smearing one
of the candidates.19
- Fake tweets have moved markets, offering the potential to
profit from digital wildfires. A Twitter user impersonating the
Russian Interior Minister Vladimir Kolokoltsev in July 2012
tweeted that Syria’s President Bashar al-Assad “has been
killed or injured”, causing crude oil prices to rise by over
US$ 1 before traders realized the news was false.20
- Thirty thousand people of Assam origin fled the tech centre
Bangalore in panic in 2012 after receiving text messages
warning that they would be attacked in retaliation for
communal violence in their home state.21,22
Section 5
When Digital Wildfires Are Most Dangerous
“Astroturfing”, Satire, “Trolling” and
Attribution Difficulties
Section 4
These are very different cases – a humorous response from a
disgruntled customer, a defamation of character and an affront to
religious sensibilities. What unites them is that hyperconnectivity
amplified their impacts to a degree that would have been
unthinkable in a pre-Internet age, when only a small number of
large organizations had the capacity to broadcast information
widely. This new reality has some challenging implications.
We should, therefore, not underestimate the risk of conflicting
false rumours, circulating within two online bubbles of
likeminded individuals, creating an explosive situation. The
extensive use of Twitter by both sides during the November 2012
clashes between Israel and Hamas in Gaza18 points to the
possibility of future situations in which competing versions of
events are propagated in self-reinforcing loops among groups of
people who are predisposed to believe one side or the other and
do not share a common information source that might help to
dissipate some of the self-amplified information loops.
Section 3
However, some individuals and organizations have suffered losses
due to the capacity for information to spread virally and globally
through social media. Some examples:
- When a musician travelling on United Airlines had his claim for
damages denied on a guitar that baggage handlers had
allegedly broken, he wrote and performed a song – “United
Breaks Guitars” – and uploaded it to YouTube, where it has
been viewed more than 12 million times. As the video went
viral, United Airlines stock dropped by about 10%, costing
shareholders about US$ 180 million.8,9
- In November 2012, the BBC broadcast an allegation that a
senior politician had been involved in child abuse, which
transpired to have been a case of mistaken identity on the
part of the victim. Although the BBC did not name the
politician, his identity was easily discovered on Twitter, where
he was named in about 10,000 tweets or re-tweets.10 On top
of pursuing legal action against all the people who spread this
false information on Twitter, the injured politician settled on
£185,000 in damages with the BBC.11
- The existence on YouTube of a video entitled “Innocence of
Muslims”, uploaded by a private individual in the United
States, sparked riots across the Middle East. These riots are
estimated to have claimed over 50 lives.12
The other dangerous situation is when information circulates
within a bubble of likeminded people who may be resistant to
attempts to correct it. In the case of the Sandy NYSE tweet,
other Twitter users rapidly posted accurate information, and
nobody had a vested interest in continuing to believe the original,
false information.16 Cases in which false information feeds into an
existing worldview, making it harder to dislodge, are far from
unimaginable. This may be more of a problem with social
networks where information is less publicly visible, for example,
through friend networks on Facebook or more “opaque” social
networks such as e-mail or text messaging.17 The spread of
misinformation in such “trusted networks” can be especially
difficult to detect and correct since recipients are more likely to
trust any information originating from within the network.
Section 2
This phenomenon has many transformative effects. Studies of
Twitter and Facebook activity in Egypt and Tunisia leave no doubt
about the role social media played in facilitating the Arab Spring.2,3
The social networking site Patientslikeme.com connects
individuals with others who have the same conditions and is
helping to expedite the development of new treatments. Analysis of
Twitter messages and networks has successfully predicted
election results,4 movie box office success5 and consumer
reactions to specific brands, among other things.6,7
Section 1
Section 3
photos depicting sharks swimming in New Jersey streets and the
Statue of Liberty with monstrous looming storm clouds. Social
media analysts say this is not surprising, as visual content tends to
spread further than text alone. In addition, the actual misinforming
tweets posted by @ComfortablySmug and @CNNweather peaked
at significantly fewer re-tweets compared to the correction posted
by @BreakingNews, even though the corrected information was
posted within an hour of the misinforming tweet.32
It is not always easy to trace the source of a digital wildfire. It would
be possible for careful cyber attackers to cover their tracks, raising
the possibility of an organization or country being falsely blamed for
propagating inaccurate or provocative information. Depending on
existing tensions, the consequences of the false attribution could
be exponentially worse than if no attribution had been made.
One can speculate that people may have been more willing to
re-tweet the photos of sharks and the Statue of Liberty because
they were harmless and surprising and, most important, had
significant entertainment value. The entertainment value may also
explain the lack of interest in circulating the correction tweets from
@BreakingNews. People may have been less prepared to re-tweet
information that could be tied to serious consequences, such as
NYSE flooding, before verifying. This suggests that norms may be
emerging, and also re-emphasizes the fact-checking responsibility
of trusted sources of information such as CNN. Slips like this could
one day be a litigation risk for media corporations.
Towards a Global Digital Ethos
Section 4
Around the world, governments are grappling with the question
of how existing laws which limit freedom of speech, for reasons
such as incitement of violence or panic, might also be applied to
online activities. Such issues can be highly controversial: in the
United Kingdom, courts initially convicted a man for making a
joke on Twitter in which he threatened to blow up an airport in
frustration at the cancellation of his flight – a conviction later
overturned on appeal.27
Establishing reasonable limits to legal freedoms of online speech
is difficult because social media is a recent phenomenon, and
digital social norms are not yet well established. The question
raises thorny issues of the extent to which it would be possible to
impose limits on the ability to maintain online anonymity, without
seriously compromising the usefulness of the Internet as a tool for
whistle-blowers and political dissidents in repressive regimes.
Section 5
Section 6
Even if the imposition of such limits were enforceable, what
authority would we trust to do it? The World Conference on
International Telecommunications in Dubai aiming to revise the
1988 treaty governing the International Telecommunications
Union28 sparked controversy in December 2012 when critics
argued that seemingly innocuous technical regulations could have
unintended negative consequences. Rules “ostensibly designed to
do everything from fight spam to ensure ‘quality of service’ of
Internet traffic could be used by individual governments to either
throttle back incoming communications or weed out specific
content they want to block”.29 As some revised treaty provisions
were believed to “give a U.N. stamp of approval to state censorship
and regulation of the Internet and private networks”,30 the United
States refused to sign the amended treaty; a decision seconded
by Canada and several European countries.31
When the incentives behind installing “quality” checks are
questionable, who can be trusted? And how do you create an
established and recognized authority that can intervene or
disrupt misinformation flows when they happen?
There are also profound questions of education and incentives.
Users of social media are typically much less knowledgeable than
editors of traditional media outlets about laws relating to issues such
as libel and defamation. Many also have less to lose than traditional
media outlets from spreading information that has not been properly
fact-checked. But there are signs that new norms may be emerging.
Figure 14 plots misinformation and correction tweets during
Hurricane Sandy in October 2012. The misinforming tweet @
ComfortablySmug’s about the NYSE floor flooding received
substantially fewer re-tweets than the tweets that circulated fake
26
Global Risks 2013
Figure 14: Re-Tweets Over Time
2000
Shark swimming in Jersey
Crazy clouds over Liberty
@comfortablysmug - NYSE flooding
1500
@cnnweather - NYSE flooding
Counts per hour
Section 2
More worrying for businesses may be misinformation that
circulates at a time when markets are already anticipating an
important announcement. On 18 October 2012, NASDAQ halted
trading on Google shares as a leaked earnings report (coupled
with weak results it entailed) triggered a US$ 22 billion plunge in
Google’s market capitalization.26 In this case, the information was
from a credible source, but it demonstrates impacts that could also
be achieved by unfortunately timed misinformation or rumours.
@BreakingNews - fixing misinformation
1000
500
30 Oct
31 Oct
Source: “#Sandy: Social Media Mapping”. Social Flow, http://blog.socialflow.com/
post/7120245759/sandy-social-media-mapping, 2012.
In addition to seeking ways to inculcate an ethos of responsibility
among social-media users, it will be necessary for consumers of
social media to become more literate in assessing the reliability and
bias of sources. Technical solutions could help here. Researchers
and developers are working on programmes and browser
extensions, such as LazyTruth,33 Truthy34 or TEASE35, that aim to
help people assess the credibility of information and sources
circulating online. It is possible to imagine the development of more
broad and sophisticated automated flags for disputed information,
which could become as ubiquitous as programmes that protect
Internet users against spam and malware.
Feedback ratings on eBay, which enable users to assess the
reliability of vendors, offer a potential template for the development
of such a service. Until now, most rating systems are limited to
specific websites – users do not carry their rating with them as a
record of credibility wherever they go online. It remains still to be
seen if that would be a desirable or feasible model. Information
disputed for ideological reasons or deliberate misattribution will
continue to pose a number of challenges; however, a system could
be developed that would trace information to its source and
provide information on whether the source was considered by a
broader community to be official. The system could also reveal
how widely the source was trusted by a spectrum of other Internet
users – all while protecting the identity of the source.
It is not yet clear what a global digital ethos would look like, or how
it could best be helped to develop. But given the risks posed by
digital wildfires in our hyperconnected world, leadership is needed
to pose these difficult questions and start the discussion.
Section 1
References
- Controlling the spread of false information online, either
through national laws or sophisticated technologies, raises
sensitive questions on the limits to the freedom of speech – a
human value that is not regarded or celebrated equally across
different societies. How can constructive international
discussions be started to define a global digital ethos without
further polarizing societies on issues of civil liberties?
- What actions can be taken to promote a new and critical
media- or information-literacy among the general public that
raises individuals’ capacities to assess the credibility of
information and its sources?
- Where should different groups of stakeholders look to verify
the source of information online? How can different markers
of trust and information quality be promulgated to facilitate
greater user clarity?
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Berthon, P.R., Pitt, L. F., Plangger, K. et al. Marketing Meets Web 2.0, Social Media, and Creative
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O’Carroll, L. “Lord McAlpine to Demand Charity Donations for False Twitter Allegations”. The
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Sweney, M. “ITV to Pay Lord McAlpine £125,000 in Damages”. The Guardian, http://www.
guardian.co.uk/media/2012/nov/22/itv-pay-lord-mcalpine-125000-damages, 2012.
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“Egypt Newspaper Fights Cartoons with Cartoons”. CBS News, The Associated Press, http://
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13.
Keller, J. “How Truth and Lies Spread on Twitter”. Bloomberg Business Week, http://www.
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Rodriguez, O.R. “Mexico Tweets Cause Massive Shootout Panic”. The Huffington Post, http://
www.huffingtonpost.com/2012/09/08/mexico-tweets-panic_n_1866941.html, 2012.
15.
Gowing, N. “Skyful of Lies and Black Swans. The New Tyranny of Shifting Information Power in
Crises”, University of Oxford, Reuters Institute for the Study of Journalism, http://reutersinstitute.
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Herrman, J. “Twitter Is A Truth Machine”. BuzzFeed, http://www.buzzfeed.com/jwherrman/
twitter-is-a-truth-machine, 2012.
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Keller, J. “How Truth and Lies Spread on Twitter”. Bloomberg Business Week, http://www.
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18.
Borger, J. “Israel and Hamas Deploy Twitter Feeds in Media War”. The Guardian, http://www.
guardian.co.uk/world/2012/nov/15/israel-hamas-twitter-media-war, 2012.
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Ratkiewicz, J., Conover, M.D., Meiss, M. et al. “Detecting and Tracking Political Abuse in Social
Media”. Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media,
http://www.aaai.org/ocs/index.php/ICWSM/ICWSM11/paper/view/2850/3274, 2011.
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Durden, T. “Fake Tweets About Syrian President Assad’s Death Cause All Too Real Spike In
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872396390443324404577595733604592276.html, 2012.
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Biswas, S. “Social Media and the India Exodus”. BBC World News, http://www.bbc.co.uk/news/
world-asia-india-19292572, 2012.
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forbes.com/sites/forbesinsights/2012/08/07/social-media-risk-is-like-wildfire-wheres-the-fireengine/, 2012.
24.
Fournier, S., Avery, J. The Uninvited Brand. In Business Horizons, 2011, 54(3):193-207.
25.
Reals, T. “Iran News Agency Picks Up “Onion” Story, Tells Iranians Rural Americans Prefer
Ahmadinejad to Obama”. CBS News, http://www.cbsnews.com/8301-202_162-57522363/
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26.
Efrati, A., “Google Hit by Weak Results, Shares Dive After Premature Report Shows
Third-Quarter Profit Sliding 20%”. The Wall Street Journal, http://online.wsj.com/article/SB10000
872396390443684104578064671358259436.html, 2012.
27.
Bowcott, O. “Twitter Joke Trial: Paul Chambers Wins High Court Appeal Against Conviction”.
The Guardian, http://www.guardian.co.uk/law/2012/jul/27/twitter-joke-trial-high-court, 2012.
28.
Waters, R., Thomas, D., Fontanella-Khan, J. “Fears Grow over Efforts to Govern the Web”. The
Financial Times, http://www.ft.com/intl/cms/s/0/7ff2be2c-3971-11e2-8881-00144feabdc0.
html#axzz2EwLdUWHr, 2012.
29.
Ibid.
30.
Nakashima, E. “U.S. Refuses to Back U.N. Treaty, Saying it Endorses Restricting the Internet”.
The Washington Post, http://www.washingtonpost.com/world/national-security/us-refuses-toback-un-treaty-saying-it-endorses-restricting-the-internet/2012/12/13/ba497952-4548-11e28e70-e1993528222d_story.html, 2012.
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Pfanner, E. “U.S. Rejects Telecommunications Treaty”. The New York Times, http://www.
nytimes.com/2012/12/14/technology/14iht-treaty14.html?_r=0, 2012.
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Lotan, G. “#Sandy: Social Media Mapping”. Social Flow, http://blog.socialflow.com/
post/7120245759/sandy-social-media-mapping#, 2012.
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Streams, K. “LazyTruth Chrome Extension Fact Checks Chain Emails”. The Verge, http://www.
theverge.com/2012/11/14/3646294/lazytruth-fact-check-chain-email, 2012.
34.
“Truthy”. Indiana University, Bloomington, http://truthy.indiana.edu/, 2012.
35.
“Tease: Trust Enabling Augmented-Reality Support for Information-Environments”. http://www.
tease-project.info/, 2012.
Shaping Culture and Governance in Digital Media
Global Risks 2013
27
Section 6
The project is being led by media, entertainment and information
industry partners from the publishing, social media, and
advertising industries joined by regulatory bodies such as the
Federal Communications Commission and the European
Commission.
Section 5
In a series of workshops held in Mexico City, Istanbul, Brussels,
New York and New Delhi, and supported by a survey on Internet
usage in 15 countries conducted in collaboration with comScore
and Oxford University, the project aims to achieve the following
over 2012 and 2013:
1. Develop an alternative framework to think about issues
relating to digital media that start with intentions of
stakeholders (e.g. reward innovation and make content
accessible) rather than the actions taken (e.g. protect
intellectual property) to arrive at a shared understanding and
framework concerning issues such as freedom of expression,
intellectual property and privacy in the digital universe.
2. Account for differences in regional values and cultures and
how they are reflected in the digital world, which is
borderless.
3. Explore the context and conditions needed for any
government or business intervention to be effective and
sustainable, showcasing some regulatory policies on
intellectual property that may have seemed effective in the
short term but too costly in the long term.
4. Highlight cases of collaborative efforts among stakeholders or
leadership of a specific group of organizations that can prove
most successful, especially relating to technological
innovation.
Section 4
Across the globe, the rules of digital content are being formed:
laws and policies written, cultural norms emerging, industry
coalitions forming. In this dynamic environment, the disparate
expectations and interests of the primary stakeholder groups
– government, industry, and citizens – are intertwined, and often
at odds. Any government policy or business strategy will need to
take into account numerous interlinked factors to achieve
desired outcomes and avoid unintended consequences.
Section 3
Box 3: Hyperconnected World
Section 2
Section 1
Section 2
The Dangers of Hubris on
Human Health
Section 3
Section 4
Humanity has always been under constant
threat from infectious disease. Globally, we
are getting better at monitoring signs of a
health-related crisis and alerting each other
– there are far fewer deaths from pandemics
today than a century ago. And modern
medicine is consistently meeting new
diseases with new treatements, as shown
by the progress on HIV since the 1980s. But
have such modern medical successes bred
a sense of hubris – excessive confidence
that science will always come to the rescue?
Challenges to human health never cease to evolve. Vaccines
and antibiotics have helped us to survive leading causes of
death from bygone eras, but we face rising rates of chronic
illnesses such as heart disease, cancers and diabetes. Although
recent pandemics, such as SARS, avian flu and swine flu, have
been contained, they also show how easily deadly viruses can
mutate and hop from other species to us.1 For all our
successes, we are never far from the edge of catastrophe, as
new biological mutations will eventually overcome a prior human
innovation.
While viruses may capture more headlines, arguably the greatest
risk of hubris to human health comes in the form of antibioticresistant bacteria. We live in a bacterial world where we will never
be able to stay ahead of the mutation curve. A test of our
resilience is how far behind the curve we allow ourselves to fall.
Section 5
Our survey respondents connected this global risk to others
including vulnerability to pandemics, failure of the international
Intellectual Property (IP) regime, rising rates of chronic disease
and unforeseen consequences of new life science technology.
Like storm systems colliding in unpredictable ways, the
unexpected interactions of these risks could overwhelm our
health systems in the coming decade and unpredictably
damage our social and economic systems.
Section 6
Figure 15: The Dangers of Hubris on Human Health Constellation
Antibiotic-resistant bacteria
28
Global Risks 2013
Section 1
Dr Margaret Chan,
Director-General, World Health Organization. March 20122
Section 4
While predicting the spread of bacteria is notoriously difficult and
complicated by a general lack of good global data, troubling
projections are emerging in regions where many efforts have
been made to better monitor the situation. Figure 16 shows the
most recent data for two resistant pathogens, as well as the
trends between 2008 and 2011. A well-known antibioticresistant bacteria – meticillin-resistant Staphylococcus aureus,
better known as MRSA – is stabilizing and possibly decreasing,
but not as sharply as had previously been projected.5 For
K. pneumoniae, there is a widespread increasing trend.ix
A post-antibiotic era means, in
effect, an end to modern medicine
as we know it. Things as common as
strep throat or a child’s scratched
knee could once again kill.
Section 3
Although several new compounds for fighting bacteria are in
development, experts caution that we are decades behind in
comparison with the historical rate at which we have discovered
and developed new antibiotics. More worryingly, none of the
drugs currently in the development pipeline would be effective
against certain killer bacteria, which have newly emerging
resistance to our strongest antibiotics (carbapenems) and fatality
rates of up to 50%.3 As shown by the death of six patients – from
18 infected – at the US National Institutes of Health in 2011,
antibiotic-resistant infections can kill, even at the world’s most
advanced medical centres.4
As a consequence, experts are starting to take seriously a
scenario in which all antibiotics are rendered ineffective for
treating even common infections.
Section 2
Many people take for granted that antibiotics will always be
available when we need them, but soon this may no longer be
the case. Every dose of antibiotics gives an advantage for those
small numbers in a bacterial population that are resistant to the
drug. The more a particular antibiotic is used, the more quickly
bacteria resistant to that antibiotic will be selected and increase
in numbers. Until now, leaders have been able to turn a blind eye
to this problem, as new antibiotics have always emerged to
replace older, increasingly ineffective ones. This is changing.
Figure 16: Percentage of Bloodstream Infections Showing Multi-Drug Resistance, EU/EEA, 2011 and Trends for 2008-2011
B. Klebsiella pneumoniae, combined resistance to
three classes of antibiotics (3rd generation cephalosporins, fluoroquinolones and aminoglycosides)
Section 5
A. Staphylococcus aureus, resistance to meticillin
(MRSA)
Percentage Resistance
< 1%
1 to < 5%
5 to < 10%
10 to < 25%
Section 6
25 to < 50%
≥ 50%
No data reported
or less than 10 isolates
Not included
The symbols and
indicate a significant increasing or decreasing trend for the period 2008-2011, respectively. These trends
were calculated on laboratories that consistently reported during 2008-2011.
Source: European Centre for Disease Prevention and Control, EARS-Net, 2012
ix
Based on the latest data (published November 2012) from the European Centres for
Disease Prevention and Control’s European Antimicrobial Resistance Surveillance
Network (EARS-Net) interactive database. http://ecdc.europa.eu/en/activities/
surveillance/EARS-net/database/Pages/database.aspx
Global Risks 2013
29
Section 1
The Costs of Antibiotic-Resistant Bacteria
Section 2
The spread of antibiotic-resistant bacteria has implications for
everyone. The impacts on human health are likely to be highest in
poorer countries, as the spread of pathogens is facilitated by
poor hygiene, polluted water supplies, overcrowding in urban
areas, civil conflicts and concentrations of people who are
immuno-compromised due to malnutrition or HIV.6 But even in
the highest-income countries, few people go through life without
needing antibiotics.
Section 3
The numbers of lives now being lost due to antibiotic-resistant
infections may seem small in comparison to heart disease and
cancer – for example, currently just under 100,000 Americans,
80,000 Chinese and 25,000 Europeans a year die from hospitalacquired antibiotic-resistant infections.7,8,9 However, experts believe
these figures from only a few years ago may be worse today. The
Global Risks report covers a 10-year time horizon, over which
timescale it is far from unrealistic to project a significant spread of
antibiotic-resistant bacteria with high mortality rates.10
It is important to remember that antibiotics are not used only to
treat infections. They also, by guarding against infection, make
possible medical procedures such as heart surgery, organ
transplantation, the survival of pre-term babies, and aggressive
immune-modulating therapy for auto-immune diseases such as
rheumatoid arthritis, as well as for cancers of the blood, bone
marrow and lymph nodes. With demographic and lifestyle
trends such as ageing populations, changes in diet and
declining rates of physical activity, we can expect rising rates of
chronic diseases which are currently treated through surgery
that would be impossible without effective antibiotics.
On top of destabilizing our health systems, there are profound
cost implications for economic systems and for the stability of
social systems. The annual cost to the US health care system of
antibiotic-resistant infections is already estimated at between
US$ 21 billion to US$ 34 billion.11 Elsewhere, losses to GDP have
already been estimated at 0.4% to 1.6%.12 The consequences of
a pandemic spread of antibiotic-resistant bacteria could also
include shortages of food due to untreatable infections in
livestock, and as leaders seek to slow the spread of pathogens,
restrictions on trade in foodstuffs, and even on travel and
migration.13 Figure 17 provides a global snapshot of the costs,
impacts and burden of antibiotic-resistant bacteria across the
globe.
Section 4
Figure 17: Spread of Antibiotic-Resistance Bacteria (ARB)x
Asia
Europe
t Thailand:>140,000!2"
INFECTIONSYRANDYR
PATIENTSDIEINPRODUCTIVITY
LOSSESYR49
s EU:!2"COSTSSOCIETY^€BNYR55
MILLIONDAYSOFLOST
PRODUCTIVITY59
Section 5
North America
s Russia:!2"AMAJORCONCERN60WITH
OFFAMILIESIMPRUDENTLYUSE
ANTIBIOTICSATHOME61
s Japan: %XTENSIVELEVELSOF!2"FOUND
IN4OKYOSURBANWATERSHED50
s China: %XTREMEOVERPRESCRIPTIONOF
ANTIBIOTICS51ANDRAPIDGROWTHRATEOF
!2"52
Middle East
& North Africa
s USA: !2"CAUSESMAJORITYOF
DEATHSYRFROMINFECTIONS
ACQUIREDINHOSPITALS56
s (EALTHCARECOSTSOF!2"ARE
s Egypt: 38%OFBLOODINFECTIONS
CONTRACTEDBYYOUNGCANCERPATIENTS
AREFROM!2"55
53BNYR56
s Israel: !2"FOUNDFATALIN^
CASESWHENRESISTANTTOOURSTRONGEST
ANTIBIOTICS63
Section 6
s Brazil: 2ATESOF!2"AREUP>60%58
s Vietnam: &ARMINGPRACTICES
CONTRIBUTINGTOSPREADOF!2"
THROUGHENVIRONMENTAL
CONTAMINATION54
s Pakistan:71%OFINFECTIONSIN
NEWBORNSAREFROM!2"55
South America
s Peru, Bolivia:>51%OFHOSPITAL
INFECTIONSCAUSEDBY!2"57
s India: 7ITHINYEARS!2"
WENTFROMBEINGRESISTANTTOTO21
DRUGS53
Sub-Saharan Africa
s Tanzania:$EATHRATEOF!2"INFECTED
CHILDRENAREDOUBLETHATOFMALARIA55
s Nigeria:2APIDSPREADOF!2"THAT
CAMETO!FRICAFROM!SIA62
Antarctica
t !2"FOUNDIN!NTARCTICANIMALS
WATERSAMPLES64
x
30
For more specific and detailed information regarding the simplified key messages outlined
in the figure, please consult the referenced papers in the chapter end notes.
Global Risks 2013
Section 1
Why Antibiotics Are Overused
Until recently, as older antibiotics have become less useful due
to the spread of resistant bacteria, new antibiotics have come
along to take their place. But the drug development pipeline for
new antibiotics has been drying out. New antibiotics have come
to market in recent years, but any sense of progress this
provides is false. Our newest antibiotics are the result of scientific
discoveries that happened decades ago. A timeline of dates of
discovery of distinct classes of antibiotics (as opposed to dates
of market introduction) illustrates that there have been no (as yet)
successful discoveries of new classes of antibiotics since 1987
(Figure 18).26 There are several competing and overlapping
explanations why.
Section 5
In many medical systems, antibiotics are not prescription-only.
They can be purchased over the counter in pharmacies or in
local marketplaces, and inappropriate self-medication is
furthering the spread of antibiotic-resistant bacteria. In India, for
example, pharmacy sales of strong antibiotics which should be a
last line of defence increased nearly sixfold from 2005 to 2010.17
Unfortunately, there is no easy answer to the question of how to
prevent excess use of antibiotics without unfairly restricting
Why the Development of New Antibiotics
Has Slowed
Section 4
Some medical systems incorporate perverse incentives for
antibiotics to be overprescribed. In China, for example, drug
sales form a significant part of hospitals’ income and, until 2010,
physicians’ pay was linked to profits from the sale of prescription
drugs. One study found that 98% of patients in a Beijing
children’s hospital were given antibiotics for a common cold.15
Figures from 2009 suggest that 74% of all hospital admissions in
China will receive antibiotics to treat their illness or as a
preventive measure.16
Meanwhile, antibiotics are over-used around the world in
livestock and fish farming (e.g. as growth promoters). Resistant
bacteria can be transferred to humans through contact with
livestock, through the food chain, and through wastewater from
these operations, as well as wastewater from hospitals and
pharmaceutical plants.20,21 One study found 45 kg of
ciprofloxacin (an antibiotic commonly used to treat bladder and
sinus infections) – the equivalent of 45,000 doses – leaking daily
from factories into a nearby river.22,23 Environmental
contamination like this has led to an antibiotic-resistant bacteria
being detected as far afield as Antarctica.24,25
Section 3
Even in systems which restrict the use of antibiotics by making
them available by prescription only, doctors can come under
pressure from patients who mistakenly believe antibiotics kill
viruses – for example, in a pan-European survey, more than 50%
of French respondents expected an antibiotic for an influenzalike illness.14 Diagnostic methods that are inadequate to
distinguish bacterial from viral infection or to specify the kind of
bacterial infection, allied with fear of medical malpractice
lawsuits, also mean that doctors tend to prescribe a cocktail of
whatever antibiotics are available in the hope that one will be
effective, especially in cases of severe infection. This imprecision
promotes further spread of resistance in bacteria.
Section 2
If we want to minimize the rate at which antibiotics become
obsolete, we should use them as sparingly as possible.
However, a combination of misaligned incentives and lack of
information has led antibiotics to be used where they are not
truly needed.
access to antibiotics in cases of genuine need. A national task
force in India recommended the end of over-the-counter sales of
antibiotics, but India’s Health Minister responded with concern
that such a move would effectively deny access to antibiotics to
patients in rural areas where there are no physicians to prescribe
the drug.18,19 Inadequate and unreliable access to a full range of
antibiotics in low- to middle-income countries is also part of the
problem. The spread of resistance in these areas is further
facilitated by illicit trade in counterfeit drugs of substandard
quality.
Figure 18: The Antibiotic Discovery Void27
The discovery dates of distinct classes of antibiotics. No new classes have been discovered since 1987.
1980
1990
199
0
19
87
1970
Lip
op
ep
tid
es
-
1960
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96
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|S M
a
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ino
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lon
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es
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ic im
ac - 1
id 96
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2000
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2010
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Am
ino
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s
-1
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-1
93
2
1930
Section 6
1920
Source: World Economic Forum, adapted from Silver, L.L. Challenges of Antibacterial Discovery. In Clinical Microbiology Reviews, 2011, 24:71-109.
Global Risks 2013
31
Section 1
Section 2
Section 3
Firstly, drugs to treat chronic illnesses such as diabetes and
hypertension increasingly offer a greater potential return on
investment for pharmaceutical companies. Unlike with
antibiotics, resistance is not an issue with these drugs. They
have the potential to rapidly achieve wide market penetration,
whereas any new antibiotic is likely to be kept as a last-resort
treatment, which will be used only for a few weeks even in that
setting, resulting in low sales for companies.28,xi
To address market failure, incentives have been suggested to
encourage pharmaceutical companies to develop more new
antibiotics.35 For example, through advance purchase
commitments, governments or philanthropists can promise to
purchase a given amount of a new drug that meets stated
criteria of effectiveness. This incentivizes private companies to
develop new antibiotics, while enabling the sales and marketing
of those new antibiotics to be restricted in the public interest.xii
Interestingly, respondents to the Global Risks Perception Survey
connected antibiotic-resistant bacteria to failure of the
international intellectual property regime. This global risk is
defined in the survey as “the loss of the international intellectual
property regime as an effective system for stimulating innovation
and investment” – that is, going beyond the mechanisms of
protecting IP to encompass the idea that the ultimate purpose of
the IP system is to stimulate worthwhile innovation. The
connection highlights a global market failure to incentivize
front-end investment in antibiotic development through the
promise of longer-term commercial reward, a failure which also
applies to drugs to fight malaria and vaccines for pandemic
influenza.29
Public-private partnerships have also shown promise in
incentivizing the development of new antibiotics. One example is
part of the Innovative Medicines Initiative (IMI), a €2 billion
initiative of the EU Commission and the European Federation of
Pharmaceutical Industries and Associations, which earmarks
funds for antibiotics discovery and development.36 The IMI acts
as a neutral third party that supports collaborative research
projects and builds networks between experts from industry
and academia.
Section 4
Secondly, regulatory burdens have also impeded development
of new antibiotics.30 Many smaller pharmaceutical companies
cannot afford the cost of meeting complex requirements for
clinical trials, and these burdens risk compromising the
development of many promising new agents.31
Thirdly, an increasing amount of effort has been invested in
exploring the potential of new life science technologies such as
genomics, nano-scale engineering and synthetic biology,
without yet yielding new approaches in the treatment of bacterial
disease. One unintended consequence of this has been to divert
researchers’ attention from the traditional approach of
discovering natural compounds to kill bacteria, which may be
getting harder.32,33
Section 5
Hubris on health not only means taking for granted that the
technologies we have will continue to work, but also assuming
that bigger and better scientific breakthroughs are just around
the corner. There is no guarantee that putative alternatives to
antibiotics will be developed before existing antibiotics become
ineffective.
What Can Be Done?
Section 6
Numerous reports, workshops and conferences have proposed
policies and strategies to address the spread of antibioticresistant bacteria. The World Health Organization (WHO)
launched a global strategy for containment of antimicrobial
resistance in 2001.34 However, a hubristic assumption that the
medical industry would continue to find solutions has
contributed to decision-makers regarding the issue as a
relatively low priority. The challenge is complicated by the fact
that antibiotic-resistant bacteria do not respect borders, so there
are limits on what can be done without strong international and
multistakeholder collaboration. An effective response to the
pandemic spread of antibiotic-resistant bacteria would involve
tackling failures of both markets and global governance.
32
Global Risks 2013
There is also potential to use public or philanthropic funding to
incentivize academic collaboration with pharmaceutical industry
researchers, and more inter-company collaboration as well.
Breakthroughs in antibiotic innovation will require pooling and
sharing of knowledge among academia, private companies and
government regulators.37 Companies and foundations like
GlaxoSmithKline (GSK) and the Bill and Melinda Gates
Foundation are pioneering an “open-lab” approach to research
which refutes the idea that secrecy and patented monopolies
are the bedrock of innovation. GSK has opened its Tres Cantos
research facilities to outside academic, government and biotech
scientists in order to collaborate on finding antibiotics, and the
Bill and Melinda Gates Foundation has “organized a tuberculosis
Drug Accelerator program that brings together research teams
from Abbott Laboratories, AstraZeneca, Bayer, Eli Lilly,
GlaxoSmithKline, Merck and Sanofi with scientists from four
academic and government institutions”.38
International efforts would be required to address licensing and
regulatory barriers to the development of new antibiotics, such
as lack of clarity and stability within the regulatory framework
and lack of harmonization in processes of clinical trials between
countries.39
Similarly, international collaboration would be required to
facilitate improvements in data gathering, to enable more
accurate and continuous monitoring of the global spread of
antibiotic-resistant bacteria.40 Experience from Europe over the
past decade shows that if data on antibiotic use and resistance
is publicly available, and national coordinated policies on
prevention and control of antibiotic-resistant bacteria are
implemented and enforced, significant reduction in antibiotic use
can be achieved in human medicine.41
xi
For the time being, priorities for R&D into new drugs are still guided by potential returns on
investments and R&D of drugs that will make peak annual worldwide sales of several billion
US dollars (e.g. for treating chronic diseases). These are preferred to new antibiotics that will
make peak annual worldwide sales of US$ 500 million to US$ 1 billion, as exemplified in
recent years by the sales of antibiotics like linezolid or daptomycin. These sales levels would
have been considered acceptable 15 years ago when a “blockbuster” was defined as a
drug making peak sales of US$ 1 billion or more annually. In 1997, the most-sold drug
(overall) had sales of US$ 3.6 billion and 28 drugs had sales of US$ 1 billion or above
(therefore considered a “blockbuster”). The most sold licensed antibiotic ranked ninth place
with sales of US$ 1.5 billion. In 2011, the most sold drug had sales of US$ 10.7 billion, and
119 drugs had sales of US$ 1 billion or above. The most-sold licensed antibiotic ranked 28
with sales of US$ 1.4 billion. (Based on expert interviews)
xii
For an overview of mechanisms to incentivize pharmaceutical R&D see Morel, C.M. and E.
Mossialos. Stocking the Antibiotic Pipeline. In BMJ, 2010, 340.48
Section 1
As new antibiotics become available, international collaboration
will be required to limit their use to cases of need. This implies
considering access to antibiotics as a development aid issue for
low- to middle-income countries, and finding international
mechanisms to promote collaboration on governance issues.
There are opportunities to learn from each others’ experience in
controlling antibiotic use through aligning financial incentives in
the health system to tackle over-prescription, through
educational interventions to tackle the problem of unnecessary
self-medication, and through improving technologies to
diagnose the existence and nature of bacterial infectionsxiv and
antibiotic stewardship.44
Figure 19: Sales of Antibiotics for Food-Producing Animals43
300
Others*
Pleuromutilins
Section 4
Sales of antibiotics for food-producing animals, including horses,
in milligrams of antibiotics per population correction unit
(PCU, i.e. 1 kilogram of animal), 2010
- How can the threat of antibiotic-resistant bacteria be
addressed, considering that it crosses both national and
species borders? How can we build visibility and political
momentum to the levels currently surrounding climate change
and pandemics?
- How do we re-establish antibiotic discovery, research and
development given the higher return on investment on R&D of
drugs for chronic diseases? What incentives are feasible?
What can facilitate the work of academia and small and
medium enterprises on antibiotics?
- How do we preserve current antibiotics until new agents are
available? How can we align incentives to tackle overuse of
antibiotics in farming of livestock and fish? What incentives
work best in health financing systems? How can the
international organizations be supported to take on a global
leadership role to preserve the utility of current antibiotics?
Section 3
The late Nobel Laureate Elinor Ostrom has compared the issue
of antibiotic-resistant bacteria to that of climate change, “in the
sense that both phenomena involve non-renewable global
resources, both are caused by human activity and are
intrinsically linked to our behaviour. The problem can only be
addressed through international cooperation”.65 A cause for
optimism is that, unlike with climate change, we know what
actions are required. The challenge is to create the will and
mechanisms to take them.45
Section 2
More efforts, however, will be needed to slow the use of
antibiotics in agriculture, aquaculture and animal husbandry.
Research is needed to understand how Nordic countries have
made significant progress – part of the answer may be small
herd sizes – and to assess what works in awareness-raising
campaigns, such as the Pew Charitable Trusts Campaign on
Human Health and Industrial Farming.xiii Figure 19 shows that the
amounts of antibiotics used to raise animals for food-production
is still high, even in highly regulated markets like Europe.42
Polymyxins
250
Aminoglycosides
Fluoroquinolones
Lincosamides
200
Macrolides
milligrams/PCU
Section 5
Trimethoprim
Sulfonamides
150
Penicillins
Tetracyclines
100
50
Section 6
Austria
Belgium
Czech Republic
Denmark
Estonia
Finland
France
Hungary
Iceland
Ireland
Latvia
Lithuania
Netherlands
Norway
Portugal
Slovenia
Spain
Sweden
United Kingdom
0
Source: Adapted from Sales of Veterinary Antimicrobial Agents in 19 EU/EEA Countries in 2010.
2012. European Medicines Agency.
xiii
xiv
Like campaigns such as ReAct-Action on Antibiotic Resistance, Antibiotic Action, and the
World Alliance against Antibiotic Resistance (WAAR), the Pew Campaign on Human Health
and Industrial Farming is working to preserve the effectiveness of antibiotics by raising
awareness and shaping international policies in all sectors. Their websites are rich in
content and information resources.
Molecular diagnostic technology available today can diagnose bacterial infections and the
sensitivity of the bacteria to various antibiotics in a very cost-effective fashion. These
technologies need to be scaled to allow for more efficient and appropriate treatment and
antibiotic usage in health systems in high-, middle- and low-income economies.
Global Risks 2013
33
Section 1
Box 4: Bringing Space Down to Earth
Section 2
Section 3
Damage to space-based infrastructure is one of the more
esoteric global risks on which our experts are surveyed annually.
Members of the World Economic Forum’s Global Agenda
Council on Space Security believe that lack of broad awareness
of the importance of satellites explains why this risk consistently
ranks at the bottom of the global risk landscape. Few people
appreciate how much we depend on satellites to support our
most critical infrastructure and to live modern and mobile lives:
- The daily operations of telephony and Internet networks,
financial markets, the banking industry, data centres and
energy networks all rely on precise timing information
conveyed by satellite.
- The €300 billion global TV industry would not be possible
without satellites.46 Nor would accurate weather predictions,
estimated to equal €60 billion in socio-economic benefits a
year in the EU alone.47
- Rescuers in emergency situations depend on satellites for
communication, when mobile networks are overloaded.
Peacekeeping and military missions also rely on secure
satellite communications.
Section 4
Satellites are at risk of three main “black swan” events which are
captured in our global risk landscape: being targeted in a conflict
between states; a strong geomagnetic storm; and collisions with
space debris. These low-likelihood but high-impact risks are,
however, not those that keep satellite operators awake at night.
They worry far more about near-term risks on Earth. As society
becomes increasingly dependent on invisible signals from
space, the unforeseen long-term consequences of shortsighted
management of the spectrum – the term for radio waves which
satellites use to communicate – threaten essential satellite
services. The desire to share scarce spectrum resources to
deliver new-age digital services is taking regulators by storm,
while invisible yet crucial services are squeezed into silence.
Section 5
Section 6
These global risks are not only physical risks to satellites but also
are risks which would greatly weaken our ability to respond and
prevent some of the most likely and high-impact global risks in
the landscape.
- Rising greenhouse gas emissions and Climate Change
Adaptation: Satellite imaging, data and communications can
be used to provide early warning systems for extreme
weather events and to monitor floods, desertification, and
rising sea levels and temperatures in real time.
- Food and water crises: Satellite imagery allows food supplies
to be tracked and the availability and quality of arable land
and potable water resources to be assessed, as well as the
locations and density of the populations that rely on them.
Satellite communications allow effective and secure food
distribution, as well as tracking for the personal safety of aid
workers who distribute it.
- Severe income disparity: Connecting the world via satellite
broadband has fundamental and far-reaching effects on
individual lives, whether by enabling universal primary
education in the most remote areas, bringing healthcare and
telemedicine to those who might otherwise die because their
homes are too far away from healthcare facilities, or making
critical solutions such as micro-finance possible in areas
where no other communications infrastructure exists.
- Critical Systems Failure: With virtually every network
infrastructure using satellite for its timing reference – whether
telephony, Internet, financial markets or banking, from data
centres to energy networks – risks to satellite infrastructure
could result in a global communications meltdown.
34
Global Risks 2013
- Land and waterway use mismanagement: Governments have
started to use satellite images in near real-time to monitor
activities such as forest clearing in the Amazon rainforest and
to identify illegal logging.
- Diffusion of weapons of mass destruction and Failure of
diplomatic conflict resolution: Satellites play a critical role in the
control of weapons of mass destruction by monitoring disarmament agreements. They can provide irreplaceable means for
improving transparency and measures for building confidence.
Through their ability to see and speak to all corners of the world,
land, air and sea, satellites are enablers that strengthen our
resilience to a wide range of global risks. Broader awareness of
this fact is needed to ensure that our critical space-based
infrastructure is managed sustainably and that we do not
underestimate the potential impacts if these critical systems fail.
Figure 20: Looking Deeper into Sea Ice
Source: “ESA satellites looking deeper into sea ice”. European Space Agency (ESA), http://
spaceinimages.esa.int/Images/2012/10/ESA_satellites_looking_deeper_into_sea_ice, 2012
Section 1
“Burden of Antibiotic Resistance”. Action on Antibiotic Resistance (ReAct), http://www.
reactgroup.org/uploads/publications/react-publications/ReAct-facts-burden-of-antibioticresistance-May-2012.pdf, 2012.
1.
Imai, M., Watanabe, T., Hatta, M., et al. Experimental Adaptation of an Influenza H5 HA Confers
Respiratory Droplet Transmission to a Reassortant H5 HA/H1N1 Virus in Ferrets. In Nature,
2012, 486:420-428.
41.
Crimmins, E.M. & Beltrán-Sánchez,H. Mortality and Morbidity Trends: Is There Compression of
Morbidity? In The Journals of Gerontology Series B: Psychological Sciences and Social
Sciences, 2011, 66B :75-86.
2.
Chan, M. “Antimicrobial Resistance in the European Union and the World”. World Health
Organization, http://www.who.int/dg/speeches/2012/amr_20120314/en/index.html, 2012.
42.
Sales of Veterinary Antimicrobial Agents in 19 EU/EEA Countries in 2010. 2012. European
Medicines Agency.
3.
Borer, A., Lisa Saidel-Odes, M. D., Riesenberg, K., et al. Attributable Mortality Rate for
Carbapenem-resistant Klebsiella Pneumoniae Bacteremia. In Infection Control and Hospital
Epidemiology, 2009, 30:972-6.
43.
Ibid.
44.
Infectious Diseases Society of America (IDSA). Combating Antimicrobial Resistance: Policy
Recommendations to Save Lives. In Clinical Infectious Diseases, 2011, 52(Suppl 5): S397-S428.
4.
Snitkin, E. S., Zelazny, A. M., Thomas, P. J., et al. Tracking a Hospital Outbreak of CarbapenemResistant Klebsiella Pneumoniae with Whole-Genome Sequencing. In Science Translational
Medicine, 2012, 4:148ra116-148ra116.
45.
46.
5.
de Kraker, M. E., Davey, P. G., & Grundmann, H. Mortality and Hospital Stay Associated with
Resistant Staphylococcus aureus and Escherichia coli Bacteremia: Estimating the Burden of
Antibiotic Resistance in Europe. In PLoS Medecine, 2011, 8:e1001104.
The Case for EPS/METOP Second Generation: Cost Benefit Analysis. March, 2012. EUMETSAT.
(pg32)
47.
6.
Laxminarayan, R. & Heymann, D.L. Challenges of Drug Resistance in the Developing World. In
BMJ: British Medical Journal, 2012, 344.
Acker, O., Pötscher, F. and Lefort, T. Why Satellites Matter: The Relevance of Commercial
Satellites in the 21st Century – A Perspective 2012-2020, 2012. Booz & Company.
48.
7.
Spellberg, B., Blaser, M., Guidos, R. J., et al. Combating Antimicrobial Resistance: Policy
Recommendations to Save Lives. In Clinical Infectious Diseases: an Official Publication of the
Infectious Diseases Society of America, 2011, 52:S397-428.
Morel, C.M. & Mossialos, E. Stocking the Antibiotic Pipeline. In BMJ: British Medical Journal,
2010, 340.
49.
Prakongsai, P., Dhammalikitkul, V., Sampradit, N. et al. “Prevention and Control of Antimicrobial
Resistance in Thailand”. Presentation at side event on antimicrobial resistance, the 65th World
Health Assembly, 2012.
50.
Ham, Y.-S., Kobori, H., Kang, J.-H. et al. Distribution of Antibiotic Resistance in Urban Watershed
in Japan. In Environmental Pollution, 2012, 162(0):98-103.
51.
Li, Y., Xu, J., Wang, F. et al. Overprescribing in China, Driven by Financial Incentives, Results in
Very High Use of Antibiotics, Injections, and Corticosteroids. In Health Affairs (Millwood), 2012,
31(5):1075-82.
52.
Zhang, R., Eggleston, K., Rotimi, V. et al., Antibiotic Resistance as a Global Threat: Evidence
from China, Kuwait and the United States. In Globalization and Health, 2006, 2(1):6.
53.
Bhattacharya, D., Sugunan, AP, Bhattacharjee, H. et al. Antimicrobial Resistance in
Shigella-Rapid Increase & Widening of Spectrum in Andaman Islands, India. In The Indian
Journal of Medical Research, 2012, 135(3):365.
54.
Hoa, P.T.P., Managaki, S., Nakada, N. et al. Antibiotic Contamination and Occurrence of
Antibiotic-Resistant Bacteria in Aquatic Environments of Northern Vietnam. In Science of the
Total Environment, 2011, 409(15):2894-2901.
55.
56.
8.
Wei, D. “Abuse of Antibiotics 80,000 Deaths Each Year”. China Youth Daily, http://zqb.cyol.com/
content/2009-01/12/content_2504156.htm, 2009.
9.
Ibid.
11.
12.
Smith, R. D., Yago, M., Millar, M., et al. Assessing the Macroeconomic Impact of a Healthcare
Problem: The Application of Computable General Equilibrium Analysis to Antimicrobial
Resistance. In Journal of Health Economics, 2005, 24:1055-75.
13.
Crimmins, E.M. & Beltrán-Sánchez, H. Mortality and Morbidity Trends: Is There Compression of
Sciences, 2011, 66B:75-86.
14.
Carlet, J., Jarlier, V., Harbarth, S., et al. Ready for a World Without Antibiotics? The Pensieres
Antibiotic Resistance Call to Action. In Antimicrobial Resistance and Infection Control, 2012, 1:11.
15.
Yezli, S. & Li, H. Antibiotic Resistance amongst Healthcare-associated Pathogens in China. In
International Journal of Antimicrobial Agents, 2012, 40:389-397.
16.
Wei, D. “Abuse of Antibiotics 80,000 Deaths Each Year”. China Youth Daily, http://zqb.cyol.com/
content/2009-01/12/content_2504156.htm, 2009.
57.
“Antimicrobial Resistance” Fact Sheet 194. World Health Organization, http://www.who.int/
mediacentre/factsheets/fs194/en/, 2012.
17.
Westly, E. India Moves to Tackle Antibiotic Resistance. In Nature, 2012, 489:192.
58.
18.
Sciences, 2011, 66B:75-86.
Rossi, F. The Challenges of Antimicrobial Resistance in Brazil. In Clinical Infectious Diseases,
2011, 52(9):1138-1143.
59.
White, A.R. Effective Antibacterials: at What Cost? The Economics of Antibacterial Resistance
and its Control. In Journal of Antimicrobial Chemotherapy, 2011, 66(9):1948-53.
19.
Westly, E. India Moves to Tackle Antibiotic Resistance. In Nature, 2012, 489:192.
60.
20.
Sciences, 2011, 66B:75-86.
Frigo, N., Unemo, M., Kubanova, A. et al. P1-S1.42 Russian Gonococcal Antimicrobial
Susceptibility Programme (RU-GASP) - Resistance Levels in 2010 and Trends during
2005–2010. In Sexually Transmitted Infections, 2011, 87(Suppl 1):A116-A117.
61.
21.
Stratchounski, L.S., Andreeva, I. V., Ratchina, S. A.et al. The Inventory of Antibiotics in Russian
Home Medicine Cabinets. In Clinical Infectious Diseases, 2003, 37(4):498-505.
62.
22.
Laxminarayan, R. & Heymann, D.L. Challenges of Drug Resistance in the Developing World. In
BMJ: British Medical Journal, 2012, 344.
Ogbolu, D.O., Daini, O.A., Ogunledun, A. et al. High Levels of Multidrug Resistance in Clinical
Isolates of Gram-Negative Pathogens from Nigeria. In International Journal of Antimicrobial
Agents, 2011, 37(1): 62-66.
23.
Joakim Larsson, D.G. & Fick, J. Transparency throughout the Production Chain—a Way to
Reduce Pollution from the Manufacturing of Pharmaceuticals? In Regulatory Toxicology and
Pharmacology, 2009, 53:161-163.
63.
Borer, A., Saidel - Odes, L., Riesenberg, K., et al. Attributable Mortality Rate for Carbapenemresistant Klebsiella Pneumoniae Bacteremia. In Infection Control and Hospital Epidemiology,
2009, 30:972-6.
24.
Sjölund, M., Bonnedahl, J., Hernandez, J., et al. Dissemination of Multidrug-Resistant Bacteria
into the Arctic. In Emerging Infectious Diseases, 2008, 14:70-2.
64.
Hernández, J., Stedt, J., Bonnedahl, J., et al. Human-associated Extended-spectrum
Beta-lactamase in the Antarctic. In Applied and Environmental Microbiology, 2012, 78:2056-8.
25.
Hernández, J., Stedt, J., Bonnedahl, J., et al. Human-associated Extended-spectrum
Beta-lactamase in the Antarctic. In Applied and Environmental Microbiology, 2012, 78:2056-8.
65.
Cars, O., A. Hedin, and A. Heddini, The Global Need for Effective Antibiotics-Moving towards
Concerted Action. Drug Resist Updat, 2011, 14(2):p. 68-9.
26.
Silver, L.L. Challenges of Antibacterial Discovery. In Clinical Microbiology Reviews, 2011,
24:71-109.
27.
Ibid.
28.
29.
Chan, M. “Strengthening Multilateral Cooperation on Intellectual Property and Public Health”.
World Health Organization, http://www.who.int/dg/speeches/2009/intellectual_
property_20090714/en/index.html, 2009.
30.
Appelbaum, P.C. 2012 and Beyond: Potential for the Start of a Second Pre-antibiotic Era? In
Journal of Antimicrobial Chemotherapy, 2012, 67:2062-8.
31.
Piddock, L.J.V. The Crisis of No New Antibiotics—What is the Way Forward? In The Lancet
Infectious Diseases, 2012, 12:249-253.
32.
Ibid.
33.
Silver, L.L. Challenges of Antibacterial Discovery. In Clinical Microbiology Reviews, 2011,
24:71-109.
34.
“WHO Global Strategy for Containment of Antimicrobial Resistance”. World Health Organization,
http://www.who.int/drugresistance/WHO_Global_Strategy.htm/en/index.html, 2001.
35.
36.
37.
Sciences, 2011, 66B:75-86.
38.
Nathan, C.F. “Let’s Gang Up on Killer Bugs”. The New York Times, http://www.nytimes.
com/2012/12/10/opinion/teaming-up-to-make-new-antibiotics.html, 2012.
39.
Section 4
10.
Section 3
40.
Section 2
References
Section 5
Section 6
Global Risks 2013
35
Section 1
Section 2
Special Report:
Building National Resilience
to Global Risks
Section 3
Section 4
As global risks can be expressed in many countries at the same
Global risks would meet with global
time, they can spread through countries that share borders,
responses in an ideal world, but the reality is have similar fundamentals or depend on the same critical
This special report is a pioneering effort to construct a
that countries and their communities are on systems.
diagnostic framework that applies the concept of “resilience” to
the frontline when it comes to systemic
assess national preparedness for global risks.
shocks and catastrophic events. In an
The proposed resilience framework would function as the “MRI” for
national decision-makers to reveal underlying weaknesses in global
increasingly interdependent and
readiness that may not be apparent via more traditional risk
hyperconnected world, one nation’s failure to risk
assessment methods. It is a prototype featuring potential qualitative
address a global risk can have a ripple effect and quantitative indicators produced by the World Economic Forum
and by other research institutions. The aim is to refine and improve
on others. Resilience to global risks –
this framework by soliciting feedback from readers of this Special
Report and then to introduce an interim finding that provides more
incorporating the ability to withstand, adapt
detail on national resilience to global risks during summer 2013.
and recover from shocks – is, therefore,
becoming more critical. This special report is Types of Risk
organized around two axioms:
xv
Section 5
- Global risks are expressed at the national
level.
- No country alone can prevent their
occurrence.
Section 6
To assess and evaluate a nation’s resilience to global risks
requires defining such risks in their most appropriate organizational context. Although this report does not differentiate between the views of a public or private sector organization, it does
underscore the importance of understanding the qualitative
distinctions among the types of risks that organizations face.1
Harvard Business School Professors Robert Kaplan and Annette
Mikes distinguish three types of risks:
1. Preventable Risks, such as breakdowns in processes and
human error
2. Strategic Risks, which are undertaken voluntarily after
weighing them against the potential rewards
3. External Risks, which are beyond one’s capacity to influence
or control
In the case of business, Kaplan and Mikes suggest that the first
two types can be approached through traditional risk management methods, focusing mostly on organizational culture and
strict compliance with regulatory, industry or institutional directives. Given the exogenous nature of external risks, cultivating
resilience is the preferred approach for this last type of risk.2
Another way of categorizing risk is to ask two questions: How
predictable is its likelihood and potential impact, and how much
do we know about how to deal with it? If we can predict it and
we know a lot about it, we can come up with specific strategies
to anticipate the risk, mitigate its effects and minimize losses. As
Figure 21 shows, resilience is most important for risks that are
difficult to predict and/or where there is little knowledge on how
to handle such risks.3
xv
36
Global Risks 2013
In this report, qualitative data refers to perception surveys.
Section 1
Emphasize resilience
High over anticipatory
strategies
Low
Strengthen
resilience
Use anticipatory
strategies
Emphasize resilience
over anticipatory
strategies
Small
Large
Amount of knowledge of a risk and effective measures to deal with it
Source: Adapted from Comfort, L. K., Boin, A., & Demchak, C. C. The Rise of Resilience, in Designing
Resilience: Preparing for extreme events. Pittsburg: University of Pittsburgh Press, 2010.
This diagnostic tool is intended to measure the resilience of a country
to global risks by treating it as a system composed of subsystems.xxi
Several methods already exist to measure the resilience of such
subsystems, mostly as they relate to the economy or ecosystem.xxii
But what makes an economic system resilient is different from what
makes an ecological system resilient (not only are the threats and
risks different, but so are the interconnections with other systems).
The aim of this report, therefore, is to present a prototype framework
to measure a country’s overall resilience via a five-part initial
framework, depicted in Figure 23. This framework considers the
country as comprised of fivexxiii core subsystems:xxiv
1. Economic subsystem: includes aspects such as the
macroeconomic environment, goods and services market,
financial market, labour market, sustainability and
productivity.10
2. Environmental subsystem: includes aspects such as
natural resources, urbanization and the ecological system.
3. Governance subsystem: includes aspects such as
institutions, government, leadership, policies and the rule of
law.
4. Infrastructure subsystem: includes aspects such as critical
infrastructure (namely communications, energy, transport,
water and health).11
5. Social subsystem: includes aspects such as human capital,
health, the community and the individual.
xvi
xvii
Figure 22: Resilient Systems
xviii
Resilience is...
xx
xix
xxi
…Bouncing back
faster after stress,
enduring greater
stresses, and
being disturbed
less by a given
amount of stress…
…Maintaining
system function
in the event
of a disturbance…
…The ability
to withstand,
recover from,
and reorganize
in response to
crises...
For an Object
For a System
For an Adaptive
System
Source: Adapted from Martin-Breen, P. & Anderies, J.M. “Resilience: A Literature Review”.
Rockefeller Foundation, http://www.rockefellerfoundation.org/news/publications/resilienceliterature-review, 2011.
xxii
xxiii
xxiv
“Stress” can imply either chronic difficulty or an acute crisis.
Systemic means “relating to a system,” especially as opposed to a particular part.
This refers to the ability of a system to continue to meet its core functions.
The current definition of resilience is a working definition.
“Systems thinking” in this context focuses on the design of systems, the flexibility and
adaptability of systems to be redesigned and their ability to redesign themselves organically in
the face of a crisis.
Many indices and studies break their topic, issue or subject into systems (terminology differs and
words such as categories, dimensions, environments or spheres have been used interchangeably).
For example: Sustainability, resilience and resource efficiency study by the Environment and Development Division, UNESCAP; the Global Political Risk Index by Eurasia Group; the Failed States Index by
The Fund of Peace; Understanding community resilience and program factors that strengthen them
by the International Federation of Red Cross and Red Crescent Societies; the Sustainability Index by
Zurich Cantonal Bank; Wealth of Nations Triangle Index by Money Matters Institute; and World
Competitiveness Scoreboard by the International Institute for Management Development.
Risk Management Index by Inter-American Development Bank assesses risk management
performance; Prevalent Vulnerability Index by Inter-American Development Bank estimates
countries’ predominant vulnerability conditions through three broad categories: (i) exposure and
susceptibility; (ii) socio-economic fragility inequality; (iii) lack of social resilience; Economic Resilience
Index by Commonwealth Secretariat/University of Malta measures countries’ resilience through four
key indicators (i) macroeconomic stability; (ii) microeconomic market efficiency; (iii) governance; (iv)
social development; Composite Vulnerability Index by Commonwealth Secretariat measures the
vulnerability of countries through three key components (i) lack of expert diversification; (ii) export
dependence; (iii) impact on natural disasters; and Environmental Sustainability Index by Yale
University/ Columbia University measures the ability of countries to protect the environment through
five core components: (i) environmental systems; (ii) environmental stresses; (iii) human vulnerability to
environmental stresses; (iv) social and institutional capacity; (v) global stewardship.
Many aspects of competitiveness are taken into account in the five core subsystems.
During 2013, workshops and expert calls will be conducted to define, verify and validate
the five core subsystems in this framework.
Global Risks 2013
37
Section 6
The working definition of a resilient country for this report is, therefore,
one that has the capability to 1) adapt to changing contexts, 2)
withstand sudden shocks and 3) recover to a desired equilibrium,
either the previous one or a new one, while preserving the continuity of
its operations.xix The three elements in this definition encompass both
recoverability (the capacity for speedy recovery after a crisis) and
adaptability (timely adaptation in response to a changing environment).
National Resilience: Five Subsystems and
Five Components
Section 5
In the wake of unprecedented disasters in recent years, “resilience”
has become a popular buzzword across a wide range of disciplines,
with each discipline attributing its own working definition to the term.
A definition that has long been used in engineering4 is that resilience
is the capacity for “bouncing back faster after stress, enduring
greater stresses, and being disturbed less by a given amount of
stress”.xvi This definition is commonly applied to objects, such as
bridges or skyscrapers. However, most global risks are systemic in
nature,xvii and a system – unlike an object – may show resilience not
by returning exactly to its previous state, but instead by finding
different ways to carry out essential functions; that is, by adapting.5
For a system, an additional definition of resilience is “maintaining
system functionxviii in the event of disturbance” (see Figure 22).
What makes a system resilient?xx Unlike an object, such as the
aforementioned bridge, systems are too complex for mathematical
calculations to predict the stresses that might arise.8 Systems
thinking provide a foundation to assess resilience through
considering such components as the system’s robustness,
redundancy, resourcefulness, response and/or recovery, all of which
are defined in the following section.9
Section 4
Resilience: A Working Definition
Resilience applies to different entities, ranging from communities to
countries, but the critical point is to avoid examining any of them in
isolation.6 We need to think of a country as a system that is
comprised of smaller systems and a part of larger systems. A
country’s resilience is affected by the resilience of those smaller and
larger systems.7
Section 3
The majority of the 50 global risks, viewed with a 10 year time
horizon, that feature annually in the World Economic Forum’s Global
Risks report fall under this categorization of risks. The 50 include
risks which could manifest either suddenly or through gradual shifts.
Although they are known risks, mapped and monitored by the
Forum’s Risk Response Network, there are varying degrees of
uncertainty regarding how and when they might manifest, especially
in this interconnected world, and regarding what primary and
secondary consequences they would have for countries.
Systems Thinking
Section 2
Predictability of Risk
Figure 21: Resilience is Most Applicable to Unpredictable
Risks with Little Knowledge About Effective Measures
Section 1
Figure 23: National Resilience Beta Framework
Macro System
Subsystems
Section 3
Components of Resilience
Section 2
Resilience
Characteristics
China
economic
Resilience
hard
landing
Performance
Country
Economic
Environmental
Governance
Infrastructure
Social
Robustness
Robustness
Robustness
Robustness
Robustness
Redundancy
Redundancy
Redundancy
Redundancy
Redundancy
Resourcefulness
Resourcefulness
Resourcefulness
Resourcefulness
Resourcefulness
Response
Response
Response
Response
Response
Recovery
Recovery
Recovery
Recovery
Recovery
Section 4
As depicted in Figure 23, each of the five subsystems is assessed
further using five components of resilience: 1) robustness, 2)
redundancy, 3) resourcefulness, 4) response and 5) recovery.xxv
These five components can be categorized further into two types:
resilience characteristics (robustness, redundancy and
resourcefulness) and resilience performance (response and
recovery). The measurement of these components presents a
significant research challenge, as there are many attributes
underpinning each of them, and these attributes are overlapping
and complementary (Appendix 3 identifies potential qualitative and
quantitative indicatorsxxvi).
Section 5
This report has adopted one approach from the World Economic
Forum’s annual Global Competitiveness Report (GCR), which
measures the microeconomic and macroeconomic foundations of
national competitiveness.xxvii Similar to the concept of national
resilience, the measurement of national competitiveness uses data
from both international sources as well as from the Forum’s annual
Executive Opinion Survey (EOS) to capture concepts that require a
more qualitative assessment, or for which internationally comparable
statistical data are not readily available. For the purposes of this
inaugural effort, we started the analysis by using data from EOS to
assess components of national resilience.xxviii
Section 6
Since 2011, the Global Competitiveness Report has included a
prototype Sustainability-Adjusted Global Competitiveness Index
(GCI).xxix This not only measures the propensity to prosper and grow
but also integrates the idea of “quality growth”, taking into account
environmental stewardship and social sustainability. The quality of
growth is an important aspect for resilience, and this will be
addressed as we develop the framework further.
xxv
xxvi
xxvii
xxviii
xxix
38
During 2013, workshops and expert calls will be conducted to define, verify and validate
the five components of resilience in this framework.
Indicators proposed are examples of currently available indices and indicators.
Since 2005, the World Economic Forum has based its competitiveness analysis on the
Global Competitiveness Index (GCI), a comprehensive tool that measures the
microeconomic and macroeconomic foundations of national competitiveness (defined as
the set of institutions, policies and factors that determine the level of productivity of a
country). The GCR aims to provide insight and stimulate discussion among all stakeholders
on the best strategies and policies to help countries to overcome the obstacles to
improving competitiveness.
The Global Competitiveness Report observed that the more competitive an economy is,
the more able it is to weather an economic crisis.
For more information, please see http://www.weforum.org/sustainablecompetitiveness.
Global Risks 2013
Resilience Characteristics (Robustness, Redundancy and
Resourcefulness)
The following three components of resilience are used to describe a
country’s state of resilience. These components should be designed
into a system and, as such, will enable assessments of a country’s
inherent resilience capabilities.12 Relevant perception data and
potential hard data for the three resilience characteristics are
available in Appendix 3.
A. Robustness
Robustness incorporates the concept of reliability and refers to the
ability to absorb and withstand disturbances and crises.13 The
assumptions underlying this component of resilience are that: 1) if
fail-safes and firewalls are designed into a nation’s critical
networks,xxx and 2) if that nation’s decision-making chains of
command become more modular in response to changing
circumstances, then potential damage to one part of a country is
less likely to spread far and wide.
Example of Attributes
- Monitoring system health: Regularly monitoring and
assessing the quality of the subsystem ensures its reliability.
- Modularity: Mechanisms designed to prevent unexpected
shocks in one part of a system from spreading to other parts
of a system can localize their impact, as happened with the
contagion from investment banking to retail banking during
the 2007-2008 financial crisis.
- Adaptive decision-making models: Networked managerial
structures can allow an organization to become more or less
centralized depending on circumstances, such as when
branch offices of the Japanese retailer Lawson’s continued
operating through the serious disruptions of the Great East
Japan Earthquake in 2011.14 These measures can include
having in place the right investment and incentive structures
to overcome competing interests.
xxx
Critical networks are not limited to ICT but included critical social, political, ecological and
economic networks.
Section 1
These two components of resilience describe how a system
performs in the event of crises. Response and recovery are
dependent on risk, event and time. These components will
provide us with the ability to compare systems and feed the
measurements and results to calibrate the resilience
characteristics. As we are dealing with global risks, the ability
to adapt the framework is also very important.
As an example of the overlapping and complementary nature
of these attributes, inclusive participation is listed as a key
attribute of response, but it is also vital in other areas such as
recovery and resourcefulness. Also inherent in all resilience
characteristics, though referenced above only in the attribute
of adaptive decision-making models, are investment and
incentive structures and design requirements to overcome
collective action problems and competing interests. There are
many individual stakeholders who would benefit from greater
shared resilience but currently lack either the incentive or feel
too pressed for time and resources to take the necessary
actions.
xxxi
xxxii
Brittle or unchangeable systems are not likely to recover well, but those that are more
flexible and willing or able to adapt to new realities are more likely to recover better.
Examples of types and applications of horizon scanning activities have been suggested by
Amanatidou, E., Butter, M., Carabias, V., et al. On Concepts and Methods in Horizon
Scanning: Lessons from Initiating Policy Dialogues on Emerging Issues. In Science and
Public Policy, 2012, 39:208-221.
Global Risks 2013
39
Section 6
Resilience Performance (Response and Recovery)
- Active “horizon scanning”: Critical to this attribute are
multistakeholder processes tasked with uncovering gaps in
existing knowledge and commissioning research to fill
those gaps.24, xxxii
- Responsive regulatory feedback mechanisms: Systems to
translate new information from horizon-scanning activities
into action – for example, defining “automatic policy
adjustments triggers” – can clarify circumstances in which
policies must be reassessed.25
Section 5
- Capacity for self-organization18: This includes factors such
as the extent of social and human capital, the relationship
between social networks and state, and the existence of
institutions that enable face-to-face networking. These
factors are critical in circumstances such as failures of
government institutions when communities need to
self-organize and continue to deliver essential public
services.
- Creativity and innovation: In countries and industries, the
ability to innovate is linked to the availability of spare
resources and the rigidity of boundaries between
disciplines, organizations and social groups.19
E. Recovery
Recovery means the ability to regain a degree of normality
after a crisis or event, including the ability of a system to be
flexible and adaptable and to evolve to deal with the new or
changed circumstances after the manifestation of a risk.23,xxxi
This component of resilience assesses the nation’s capacities
and strategies for feeding information into public policies and
business strategies, and the ability for decision-makers to take
action to adapt to changing circumstances.
Section 4
C. Resourcefulness
Resourcefulness means the ability to adapt to crises, respond
flexibly and – when possible – transform a negative impact into
a positive.16 For a system to be adaptive means that it has
inherent flexibility, which is crucial to enabling the ability to
influence of resilience.17 The assumption underlying this
component of resilience is that if industries and communities
can build trust within their networks and are able to selforganize, then they are more likely to spontaneously react and
discover solutions to resolve unanticipated challenges when
larger country-level institutions and governance systems are
challenged or fail.
- Communication: Effective communication and trust in the
information conveyed increase the likelihood that, in the
event of a crisis, stakeholders are able to disseminate and
share information quickly, and to ensure cooperation and
quick response from the audience.
- Inclusive participation: Inclusive participation among public
sector, private sector and civil society stakeholders can
build a shared understanding of the issues underpinning
global risks in local contexts, reduce the possibility of
important interdependencies being overlooked,21 and
strengthen trust among participants.22
Section 3
Examples of Attributes
- Redundancy of critical infrastructure: Designing replication
of modules which are not strictly necessary to maintaining
core function day to day, but are necessary to maintaining
core function in the event of crises.
- Diversity of solutions and strategy: Promoting diversity of
mechanisms for a given function. Balancing diversity with
efficiency and redundancy will enable communities and
countries to cope and adapt better than those that have
none.
D. Response
Response means the ability to mobilize quickly in the face of
crises.20 This component of resilience assesses whether a
nation has good methods for gathering relevant information
from all parts of society and communicating the relevant data
and information to others, as well as the ability for decisionmakers to recognize emerging issues quickly.
Section 2
B. Redundancy
Redundancy involves having excess capacity and back-up
systems, which enable the maintenance of core functionality
in the event of disturbances.15 This component assumes that a
country will be less likely to experience a collapse in the wake
of stresses or failures of some of its infrastructure, if the design
of that country’s critical infrastructure and institutions
incorporates a diversity of overlapping methods, policies,
strategies or services to accomplish objects and fulfil
purposes.
Section 1
Qualitative Assessment of National
Resilience
Figure 24: Resilience Question may be a Potential Variable for
Recovery Component of Resilience
Country
Section 2
As a first step towards developing the diagnostic framework, we
have begun to explore perception survey data in assessing
resilience. This year, the World Economic Forum introduced
questions about resilience into two of its global surveys: 1) the
Global Risks Perception Survey (GRPS) measured the
perceptions of the Forum’s expert network about their
nation’sxxxiii resilience to global risks; and 2) the Executive
Opinion Survey (EOS) introduced a question to assess a
government’s effectiveness in managing risks in 2012.26
Section 3
The qualitative assessment will be coupled with a quantitative
one that includes statistical data by country.xxxiv This will result in
a rating that combines perception data and objective data (i.e.
qualitative and quantitative data), and that enables an analysis of
patterns among resilience, risk management, competitiveness
and sustainability (see Appendix 3 for examples). Our working
hypothesis is that if leaders wish to assess the potential support
for improving their country’s resilience, then perception surveys
are a good place to start.
Economic
Governance
Infrastructure
Social
Robustness
Robustness
Robustness
Robustness
Robustness
Redundancy
Redundancy
Redundancy
Redundancy
Redundancy
Resourcefulness
Resourcefulness
Resourcefulness
Resourcefulness
Resourcefulness
Response
Response
Response
Response
Response
Recovery
Recovery
Recovery
Recovery
Recovery
Figure 25: Countries’ Ability to Adapt and Recover from
Economic and Environmental Risksxxxviii
Brazil
Global Risks Perception Survey (GRPS): Resilience
Question
Germany
xxxv
Section 4
Over 1,000 respondents to the GRPS were asked, per risk
and regarding their country of expertise:
“If this risk materialized in your country* of expertise, what is the
ability of the country to adapt and/or recover from the impact?”
Environmental
India
Italy
Japan
People’s Republic of China
(*Your country refers to the country you selected in the respondent’s
information page.)
Russian Federation
Switzerland
Section 5
This question enables us to understand respondents’
perceptions of the ability of a country to adapt and/or recover
from the impact of global risks. In the survey, respondents
assess this ability against all five categories of global risks:
economic, environmental, geopolitical, societal and
technological. Assuming, economic global risks will highly
impact the country’s economic subsystem, and environmental
global risks will highly impact the country’s environmental
subsystem (see Figure 24).xxxvi This section focuses on analyzing
how these country subsystems are expected to recover after a
crisis caused by economic and environmental global risks.
Section 6
Data collected from the current GRPS gave us sufficient
responses for the analysis of 10 countries: Brazil, China,
Germany, India, Italy, Japan, Switzerland, Russia, the United
Kingdom and the United States.27,xxxvii Figure 25 illustrates these
countries’ ability to recover from and adapt to economic and
environmental risks respectively.
United Kingdom
USA
1
1.5
2
2.5
3
3.5
4
4.5
Country Recovery/Adaptation
Economic Risks
Environmental Risks
Margin of Error (95% confidence)
Switzerland was perceived as having the highest ability to adapt
and/or recover from economic and environmental global risks;
both Italy and India were rated relatively low. Japan was seen to
have a comparable ability to Switzerland to adapt and recover
from environmental risks, but lower in terms of economic risks.
This may be a reflection of frustration about Japan’s economic
position and the risk of recession.
The question from the GRPS is one indicator for the response
component of the proposed resilience framework. It represents
the way respondents perceive their country’s ability to adapt to
and/or recover from certain types of global risks. In building a
framework for National Resilience, further analysis will provide
insights into areas needing greater investment and resources to
build resilience.
xxxiii
xxxiv
xxxv
xxxvi
xxxvii
40
Country is the country of expertise.
Statistical data may be obtained from open-source databases and other indices. See
Appendix 3 for more potential qualitative and quantitative indicators identified.
The Global Risks Perception Survey is a major input into the annual Global Risks Report.
See Appendix 1.
Further work will try to identify how one type of risk can affect multiple or all of the country’s
subsystems, not just the subsystems from which the risk originally manifested itself.
These countries had a calculated margin of error smaller than 0.5 units. Please see
Appendix 3 for more details on sample size and margin of errors for these and other
countries.
Global Risks 2013
xxxviii
The error bars in the figure indicate the margin of error for each country per category (at a
95% confidence level).
Section 1
Executive Opinion Survey: Risk Management Effectiveness
Question
Figure 27: Government’s Risk Management Effectiveness and
the Country’s Overall Competitiveness Score
Over 14,000 respondents to the Executive Opinion Survey
(EOS)xxxix were asked:
5.2
Europe
South America
Switzerland
Asia
4.6
United States
China
4.4
India
Italy
4.2
Brazil
4
3.8
Japan
Russian Federation
3.6
3.4
3.4
3.6
3.8
4
4.2
4.4
4.6
4.8
5
5.2
5.4
5.6
5.8
Section 3
Research28 has linked the ability to respond effectively and
efficiently during a crisis with good risk management, which cuts
across all five subsystems. The question above from the EOS
collected perceptions from business managers about their
government’s risk-management effectiveness. Therefore, for the
purpose of this analysis, we focus on the governance subsystem
and response component of resilience, as illustrated in Figure 26.
Germany
United Kingdom
North America
4.8
Section 2
“How would you assess your national government’s overall risk
management effectiveness of monitoring, preparing for,
responding to and mitigating against major global risks (e.g.
financial crisis, natural disasters, climate change, pandemics,
etc.)? (1 = Not effective in managing major global risks; 7 =
Effective in managing major global risks)”
Government’s risk management effectiveness
5
6
Global Competitiveness Index Score
Figure 26: Government’s Risk Management Effectiveness may
be a Potential Variable for the Response Component of the
Governance Subsystem.
Country
Environmental
Governance
Infrastructure
Social
Robustness
Robustness
Robustness
Robustness
Redundancy
Redundancy
Redundancy
Redundancy
Redundancy
Resourcefulness
Resourcefulness
Resourcefulness
Resourcefulness
Resourcefulness
Response
Response
Response
Response
Response
Recovery
Recovery
Recovery
Recovery
Recovery
The most related questions seem to be intuitively what one
might expect. Of the seven indicators, the most highly
correlated question is that on leadership, i.e. a politician’s ability
to govern. This corroborates the message about leadership in
risk management at the country level of the Global Risks 2012
report special feature on The Great East Japan Earthquake. It
also underscores the recommendation from the Global Risks
2007 report to establish the role of National Risk Officers.xlii
Other interesting relationships highlighted above were with
business-government relations and government provision of
services for improved business performance. These
relationships require further analysis but they may indicate the
ability to share information effectively to improve monitoring and
risk preparedness. By assessing government wastefulness,
reform-process efficiency and corruption, we may be able to
deduce that effective risk management practices are likely to be
transparent and adaptive.
The analysis in this subsection is an initial indication for how we
intend to proceed with building the National Resilience Rating. It
is also a step towards understanding how questions from the
GRPS and the EOS may identify indicators for the different
components of resilience, which will be further complemented
with quantitative data in the interim report in summer 2013.
xli
xxxix
xl
The Executive Opinion Survey is carried out among CEOs and top executives and is a
major input into the annual Global Competitiveness Report and the Global
Competitiveness Index, and Sustainable Competitiveness work. http://www.weforum.org/
globalcompetitiveness
These countries had sufficient sample sizes.
xlii
Analysis has shown that there are strong relationships between most of the questions
(other than the risk management question) in the Executive Opinion Survey.
A Country Risk Officer – analogous to Chief Risk Officers in the corporate world – would be
the focal point for managing a portfolio of risk across disparate interests, setting national
prioritization of risk and allowing governments to engage in the forward action needed to
begin managing global risks rather than merely coping with them.
Global Risks 2013
41
Section 6
Figure 27 demonstrates that there may be a link between a
government’s risk management effectiveness and that
country’s overall competitiveness. As observed, a country with
high risk-management effectiveness appears to have scored
highly in competitiveness, and a country with low riskmanagement effectiveness appears to have scored low in
competitiveness (except Japan). From further analysis of the
EOS question on the 10 countries from the Global Risks
Survey,xl we can see that governments in Germany, Switzerland
and the United Kingdom are perceived by business leaders to
have comparatively high risk-management effectiveness. While
India and Italy scored relatively lower on the GRPS output,
Russia was seen as having the least effective risk management
based on the EOS responses. In addition, although in Figure 25
Japan was seen to have greater ability to recover from
environmental risks, its government’s risk-management
effectiveness was rated poorly in comparison to other
countries’.
Politicians’ ability to govern
Business-government relations
Reform implementation efficiency
Public trust of politicians
Wastefulness of government spending
Measures to combat corruption and bribery
Government provision of services for improved business
performance
Section 5
Robustness
-
Section 4
Economic
Additional analysis revealed other potential indicators that may
be linked to risk management, which will require further
scrutiny. Correlation analysis showed there were moderate
relationships between the government’s risk management
effectiveness and the following seven indicators from the EOS
(Further details are available in Appendix 3).xli
Section 1
Next Steps Towards a National
Resilience Rating
Section 2
As early as 2007, the Global Risks report suggested the creation
of the role of Country Risk Officer. The national resilience rating
proposed in this Special Report would enable such officers and
other decision-makers to benchmark and track a nation’s level
of resilience, understand the balance that needs to be struck
between resilience and other goals, and identify areas that may
require further investment.
Section 3
For example, the national resilience rating will also help decisionmakers to think about resilience in supply chains.xliii According to
the World Economic Forum’s Dynamic Resilience in Supply
Chain project, this is rising to the top of the political and
executive agendas in the wake of recent major disruptions, but
there remains a reluctance to invest in resilience due to lack of
good data (see Box 5).
There is also a lack of knowledge about practical actions that
leaders can take to build resilience. To tackle this shortfall, the
Risk Response Network has built its Resilience Practices
Exchange (RPE)xliv using the latest social network technology,
which will build and share knowledge about effective practices
online (see Box 6).
Section 4
More broadly, the Risk Response Network’s goal is to build a
common discussion framework in the global community,
nurturing a culture of risk and resilience awareness across
stakeholder groups. We invite readers of this Special Report to
contact us at http://www.weforum.org/globalrisks2013 or at
rrn@weforum.org with suggestions on how to approach
measuring national resilience.
Box 5: Supply Chain Risk Initiative
Launched by the World Economic Forum in May 2011, the
Supply Chain Risk Initiative (SCRI) addresses the need for a
better risk-based approach for safeguarding global supply
chains and published the report “New Models for Addressing
Supply Chain and Transport Risk” in 2012. US Secretary of
Homeland Security Janet Napolitano also joined the call for
increased global dialogue by launching at the Annual Meeting
2012 in Davos-Klosters the first US Strategy for Global Supply
Chain Security.
Phase I of the work brought agreement on priorities and
recommendations for action:
1. Improve international and interagency compatibility of
resilience standards and programmes
2. More explicitly assess supply chain and transport risks as
part of procurement, management and governance
processes
3. Develop trusted networks of suppliers, customers,
competitors and government focused on risk management
4. Improve network risk visibility, through two-way information
sharing and collaborative development of standardized risk
assessment and quantification tools
5. Improve pre- and post-event communication on systemic
disruptions and balance security and facilitation to bring a
more balanced public discussion
Phase IIxlv of the Supply Chain Risk Initiative entailed regional
workshop across Asia, Europe and North America which
brought together supply chain and risk experts from across
government and industry to:
Section 5
- Deepen collective understanding of the risk and threat
landscape
- Work towards a blueprint for a resilient global supply chain
- Improve transparency across supply chains.
Section 6
Addressing the vulnerabilities identified in Phase I (e.g. reliance
on oil and weak information flow), Phase II focused on shared
efforts to build resilience. Resilience has been the core focus as
risk assessment goes hand in hand with resilience it has
implications to the strategy of governments and organizations.
The Forum identified measures such as improving information
sharing between governments and businesses, harmonizing
legislative standards and building a common risk assessment
framework for building resilient supply chains.
Development of risk assessment framework is critical to improve
supply chains adaptability to build resilience. The core
components are data and information sharing for improved
visibility along the supply chain.
xliii
xliv
42
The World Economic Forum’s findings in “Dynamic Resilience in Supply Chains” provide
multiple working definitions, which include concepts related to the ability to reorganize and
deliver core function continually, to bounce back from large scale disruptions, and to build
capacity through collective and simultaneous efforts.
For more details, please refer to the box on the Resilience Practices Exchange.
Global Risks 2013
xlv
The initiative’s Phase II report, “Dynamic Resilience in Supply Chains”, is scheduled for a
launch at the January 2013 Annual Meeting in Davos-Klosters. To learn more about the
initiative please visit http://www.weforum.org/supplychain.
Section 1
Box 6: Resilience Practices Exchange (RPE) Box 7: One Year On Resilience Practices
The Resilience Practices Exchange (RPE) is an initiative of the
World Economic Forum to share insights and ideas that improve
national and organizational resilience to global risks.
Figure 28: Resilience Practices Exchange Process
Contribute
Practices
Discuss
Evaluate
Practices
Innovate
The RPE is a secure platform currently accessible only by
members of the Forum’s Risk Response Network and Network of
Global Agenda Councils. The RPE may be accessed through a
secure and trusted online platform of the World Economic Forum.xlvi
For the full case responses, please refer to the following
webpage, http://www.weforum.org/globalrisks2013/
followup2012.
Section 6
Examples of Resilience Building Practices
- The G20 establishing the cross-border Financial Stability
Board (FSB): A regulatory body to coordinate financial
services regulators and international standard-setting bodies
across borders and organizations.
- The Indonesian government response to the 2004 Tsunami in
Aceh Province, Indonesia: After the 2004 Indian Ocean
tsunami and earthquake, the Government of Indonesia set up
a pragmatic and region-based agency to effectively lead the
relief efforts in the province of Aceh.
- Governmental cyber risk information-sharing partnerships:
Governments are setting up agencies to share information
with international partners, including overseas governments,
agencies and businesses to provide an international,
informed response to cyber risks.
Please contact resilience.exchange@weforum.org for further
information.
xlvi
Section 5
The aim is to develop a process that takes a suggested practice
through a community discussion phase and then on to a process
of evaluation and innovation to improve that practice. This is
limited not only to the online exchange but can also involve
in-person meetings, virtual meetings, workshops and other forms
of engagement with the Forum’s Risk Response Network.
Section 4
Explore
Section 3
Exchange
World Economic Forum’s Risk Response Network, in
collaboration with PwC, has revisited the three cases in the
Global Risks 2012 report – Seeds of Dystopia, How Safe are Our
Safeguards? and The Dark Side of Connectivity – to analyse
practices to improve resilience against the risks highlighted in
each case, available on our interactive website.
- Seeds of Dystopia (with further collaboration from Eurasia
Group): As fiscal, ageing and employment trends combine to
threaten the emergence of a new class of fragile states, the
private sector, civil society, local and national governments,
as well as multilateral organizations need to work in concert
to create a modern and sustainable social contract. The
resilience practices highlighted here are engaging multiple
stakeholders in solutions based on holistic insights;
continuous monitoring of trends to enable assumptions to be
revisited; promoting open and inclusive attitudes towards
immigrants; and embracing innovative financing models.
- How Safe are Our Safeguards? Jurisdictional safeguards
against cross-border risks can quickly become outdated in
an interdependent and rapidly changing environment.
Practices that improve resilience can be found by looking for
common threads in two very different areas – financial system
stability and pandemic influenza. The resilience-enhancing
practices highlighted are: revisiting underlying assumptions
related to safeguards in place; introducing forward-looking
elements such as stress testing and scenario planning into
safeguard development; leveraging incentives; and promoting
cross-border collaboration among governments and other
organisations.
- The Dark Side of Connectivity: In an increasingly
hyperconnected world, the impacts of our successes and
mistakes are significantly magnified. Resilience of cyberspace
could be strengthened by treating cyber security as a
board-level issue within organisations; establishing
mechanisms for governments and private companies to
share information in a trusted space, and for governments to
collaborate in emergency cyber-attack situations; and
designing devices and systems that incorporate as much
protection as possible against inevitable human error.
Section 2
By providing an online, interactive repository of ideas, the RPE
aims to improve resilience to global risks within organizations,
industries and countries, as well as across economic,
environmental, geopolitical, societal and technological areas. A
digital platform enables a diverse community of experts to
contribute, discuss and explore various existing practices as a
basis for further exchange, evaluation and innovation (Figure 28).
Practices to Improve Resilience from the 2012 Risk Cases
For more information, please see http://rpe.weforum.org.
Global Risks 2013
43
Section 1
References
Section 2
Section 3
Section 4
Kaplan, R.S. & Mikes, A. Managing Risks: A New Framework. In Harvard Business Review, 2012.
2.
Ibid.
3.
Comfort, L. K., Boin, A., & Demchak, C. C. The Rise of Resilience, in Designing Resilience:
Preparing for Extreme Events. Pittsburg: University of Pittsburgh Press, 2010.
4.
Ibid. Martin-Breen, P. & Anderies, J.M. “Resilience: A Literature Review”. Rockefeller Foundation,
http://www.rockefellerfoundation.org/news/publications/resilience-literature-review, 2011; and
Longstaff, P.H. “Security, Resilience, and Communication in Unpredictable Environments Such
as Terrorism, Natural Disasters, and Complex Technology”. Harvard University Center for
Information Policy Research, http://pirp.harvard.edu/pubs_pdf/longsta/longsta-p05-3.pdf,
2005.
5.
Berkes, F. Understanding Uncertainty and Reducing Vulnerability: Lessons from Resilience
Thinking. In Natural Hazards, 2007, 41:283-295.
6.
Fiksel, J. Sustainability and Resilience: Toward a Systems Approach. In Sustainability: Science,
Practice and Policy, 2006, 22:14-21.
7.
Holling, C.S. Understanding the Complexity of Economic, Ecological, and Social Systems. In
Ecosystems, 2001, 4:390-405; and Walker, B., Holling, C. S., Carpenter, S. R., & Kinzig, A.
Resilience, Adaptability and Transformability in Social-ecological Systems. In Ecology and
Society, 2004, 9.
8.
Holling, C.S. From Complex Regions to Complex Worlds. In Ecology and Society, 2004, 9;
Holland, J.H. Studying Complex Adaptive Systems. In Journal of Systems Science & Complexity,
2005, 19:1-8; and Folke, C. Resilience: The Emergence of a Perspective for Social-ecological
Systems Analyses. In Global Environmental Change, 2006, 16:253-267.
9.
Bruneau, M., Chang, S. E., Eguchi, R. T., et al. A Framework to Quantitatively Assess and
Enhance the Seismic Resilience of Communities. In Earthquake Spectra, 2003, 19:733; and
Bruneau M. Seismic Resilience of Communities-conceptualization and Operationalization. In
International Workshop on Performance-based Seismic-Design, 2004.
10.
The Global Competitiveness Report 2011-2012. 2011. Geneva: World Economic Forum.
11.
OECD Studies in Risk Management: Innovation in Country Risk Management. 2009. Paris:
Organisation for Economic Co-operation and Development.
12.
13.
Enhance the Seismic Resilience of Communities. In Earthquake Spectra, 2003, 19:733.
14.
Global Risks 2012. 2012. Geneva: World Economic Forum.
15.
16.
Ibid.
17.
Walker, B. H., Abel, N., Anderies, J. M., & Ryan, P. Resilience, Adaptability, and Transformability
in the Goulburn-broken Catchment, Australia. In Ecology and Society, 2009, 14:12.
18.
19.
Swanson, D., Barg, S., Tyler, S., et al. Seven Guidelines for Policy-Making in an Uncertain World.
In Creating Adaptive Policies: a Guide for Policy-Making in an Uncertain World, Swanson D. and
Bhadwal S., (eds). 2009, Sage: London.
20.
21.
Ozdemir, V. and Knoppers, B.M. From Government to Anticipatory Governance: Responding to
the Challenges of Innovation and Emerging Technologies. In Governance for Health, Kickbusch,
I. and Gleicher, D. (eds). (In Press), Springer: New York.
22.
Bhadwal S., (eds). 2009, Sage: London; Kickbusch, I. & Gleicher, D. “Governance for Health in
the 21st Century”. World Health Organization, http://www.euro.who.int/__data/assets/pdf_
file/0010/148951/RC61_InfDoc6.pdf, 2012; and Klijn, E.-H. Trust in Governance Networks:
Looking for Conditions for Innovative Solutions and Outcomes. In The New Public Governance?
Emerging Perspectives on the Theory and Practice of Public Governance, S.P. Osborne (ed).
2009, Routledge: London.
23.
24.
Amanatidou, E., Butter, M., Carabias, V., et al. On Concepts and Methods in Horizon Scanning:
Lessons from Initiating Policy Dialogues on Emerging Issues. In Science and Public Policy, 2012,
39:208-221.
25.
Bhadwal S., (eds). 2009, Sage: London.
26.
The Global Competitiveness Report 2011-2012. 2011. Geneva: World Economic Forum.
27.
Malleret, T. & Cleary, S. Resilience to Risk. Cape Town: Human and Rousseau, 2006.
28.
Ibid. “Preemptive Risk Management Strategies: Advance Recovery and the Development of
Resilient Organisations and Societies”. In Integrative Risk Management: Advanced Disaster
Recovery Risk Dialogue Series, Swiss Reinsurance Company Ltd, http://www.hks.harvard.edu/
var/ezp_site/storage/fckeditor/file/pdfs/centers-programs/programs/crisis-leadership/
Risk_Dialogue_Ch%202.pdf, 2010; and Kunreuther, H. & Useem, M. Learning from
Catastrophes: Strategies for Reaction and Response. New Jersey: Pearson Education, Inc,
2010.
Section 5
1.
Section 6
44
Global Risks 2013
Section 1
Survey Findings
Section 2
The Risk Landscape
Section 3
For each of the 50 global risks, respondents were asked to
assess, on a scale from 1 to 5, the likelihood of the risks
occurring over the next 10 years and the impact if the risk were
to occur.
Figure 29 indicates the average values of these two measures
for each of the 50 global risks in their respective categories (see
also Figure 2 the Global Risks Landscape scatterplot, showing
them in one combined graph). Almost all dots on the scatterplots
are above and to the right of the midpoints (at 3 or more) of the 1
to 5 axes, suggesting that the majority of the 50 global risks
were rated, on average, as having high likelihood and impact.
Section 5
Nonetheless, there is some interesting variation in the dots’
placement on the landscape. Some economic risks, such as
major systemic financial failure, chronic fiscal imbalances and
severe income disparity are far out towards the top-right hand
corner, with impact and likelihood scores around 4 (on a scale
from 1 to 5, which is high for an average ranking). Some of the
technological risks are closer to the middle of the axes, with
impact and likelihood scores 3 or less.
Section 4
In this section, the results from the annual
Global Risks Perception Survey are presented
in detail. They collate the views of more than
1,000 experts from the World Economic
Forum’s communities. Respondents are aged
between 19 and 79, come from different types
of organizations, different fields of specialist
knowledge, and from over 100 countries.xlvii
As was observed in previous editions of the Global Risks report,
there appears to be a strong relationship between the likelihood
and impact. The dots seem to line up loosely around the
45-degree line and there are no dots in the bottom-right or
top-left corners of the plot. Survey respondents seem to be
associating high-likelihood events with high impacts.
Still it is interesting to observe how for some risks, particularly
technological risks such as critical systems failure, the answers
are more distributed than for others – chronic fiscal imbalances
are a good example. It appears that there is less agreement
among experts over the former and stronger consensus over
the latter.
xlvii
See Appendix 1 for a more detailed description of the sample.
Global Risks 2013
45
Section 6
This finding holds up even when looking at individual responses
for each of the risks, and not only average numbers. The
colourful tiles in Figure 30 show how the responses are
distributed across the scatterplot for each of the 50 risks. While
there were some responses that were off the 45-degree line, the
combinations of impact and likelihood that got the most votes
from survey respondents – as indicated by the dark-coloured
tiles – seem to be near that diagonal in almost all of the 50
diagrams.
Section 1
Figure 29: Global Risks Landscape by Categories and their Descriptions
Economic
Chronic fiscal imbalances
Failure to redress excessive government debt obligations.
2
Chronic labour market
imbalances
A sustained high level of underemployment and
unemployment that is structural rather than cyclical in nature.
3
Extreme volatility in
energy and agriculture
prices
Severe price fluctuations make critical commodities
unaffordable, slow growth, provoke public protest and
increase geopolitical tension.
4
Hard landing of an
emerging economy
The abrupt slowdown of a critical emerging economy.
5
Major systemic financial
failure
A financial institution or currency regime of systemic
importance collapses with implications throughout the global
financial system.
6
Prolonged infrastructure
neglect
Chronic failure to adequately invest in, upgrade and secure
infrastructure networks.
7
Recurring shortages of financial resources from banks and
capital markets.
8
Widening gaps between the richest and poorest citizens.
9
Unforeseen negative
consequences of
regulation
Regulations which do not achieve the desired effect, and
instead negatively impact industry structures, capital flows
and market competition.
10
Unmanageable inflation
or deflation
Failure to redress extreme rise or fall in the value of money
relative to prices and wages.
1
Growing resistance of deadly bacteria to known antibiotics.
2
Failure of climate change
adaptation
Governments and business fail to enforce or enact effective
measures to protect populations and transition businesses
impacted by climate change.
3
Air, water or land permanently contaminated to a degree that
threatens ecosystems, social stability, health outcomes and
economic development.
4
mismanagement
Deforestation, waterway diversion, mineral extraction and
other environment modifying projects with devastating
impacts on ecosystems and associated industries.
5
Poorly planned cities, urban sprawl and associated
infrastructure that amplify drivers of environmental
degradation and cope ineffectively with rural exodus.
6
Persistent extreme
weather
Increasing damage linked to greater concentration of
property in risk zones, urbanization or increased frequency
of extreme weather events.
7
Rising greenhouse gas
emissions
Governments, businesses and consumers fail to reduce
greenhouse gas emissions and expand carbon sinks.
8
Threat of irreversible biodiversity loss through species
extinction or ecosystem collapse.
9
Unprecedented
geophysical destruction
Existing precautions and preparedness measures fail in the
face of geophysical disasters of unparalleled magnitude such
as earthquakes, volcanic activity, landslides or tsunamis.
10
Vulnerability to
geomagnetic storms
Critical communication and navigation systems disabled by
effects from colossal solar flares.
1
A weak state of high economic and geopolitical importance
that faces strong likelihood of collapse.
2
Diffusion of weapons of
mass destruction
The availability of nuclear, chemical, biological and radiological
technologies and materials leads to crises.
3
Entrenched organized
crime
Highly organized and very agile global networks committing
criminal offences.
4
conflict resolution
The escalation of international disputes into armed conflicts.
5
Global governance
failure
Weak or inadequate global institutions, agreements or networks,
combined with competing national and political interests, impede
attempts to cooperate on addressing global risks.
6
Targeting of commercial, civil and military space assets and
related ground systems that can precipitate or escalate an
armed conflict.
7
corruption
The widespread and deep-rooted abuse of entrusted power
for private gain.
8
Terrorism
Individuals or a non-state group successfully inflict large-scale
human or material damage.
9
Unilateral resource
nationalization
Unilateral moves by states to ban exports of key commodities,
stockpile reserves and expropriate natural resources.
10
Unchecked spread of illegal trafficking of goods and people
throughout the global economy.
5
4
1
3
Section 2
8
2
7
10
3.5
Section 3
1
4
6
9
3
2.5
2.5
3
3.5
4
Environmental
Section 4
4
2
3
7
6
4
1
Section 5
3.5
5
8
9
10
3
2.5
2.5
3
3.5
4
4
2
5
4
8
1
3.5
7
10
Section 6
Geopolitical
6
3
10
3
2.5
2.5
3
3.5
46
Global Risks 2013
4
Section 1
Societal
4
Backlash against
globalization
Resistance to further increased cross-border mobility of
labour, goods and capital.
2
Inadequate or unreliable access to appropriate quantities and
quality of food and nutrition.
3
Ineffective illicit drug
policies
Continued support for policies that do not abate illegal drug
use but do embolden criminal organizations, stigmatize drug
users and exhaust public resources.
4
Mismanagement of
population ageing
Failure to address both the rising costs and social challenges
associated with population ageing.
5
Rising rates of chronic
disease
Increasing burden of illness and long-term costs of treatment
threaten recent societal gains in life expectancy and quality.
6
Rising religious
fanaticism
Uncompromising sectarian views that polarize societies and
exacerbate regional tensions.
7
Unmanaged migration
Mass migration driven by resource scarcity, environmental
degradation and lack of opportunity, security or social stability.
8
Unsustainable
population growth
Unsustainably low or high population growth rates and sizes,
creating intense and rising pressure on resources, public
institutions and social stability.
9
Vulnerability to
pandemics
Inadequate disease surveillance systems, failed international
coordination and the lack of vaccine production capacity.
10
Water supply crises
Decline in the quality and quantity of fresh water combine with
increased competition among resource-intensive systems,
such as food and energy production.
1
Single-point system vulnerabilities trigger cascading failure of
critical information infrastructure and networks.
2
Cyber attacks
State-sponsored, state-affiliated, criminal or terrorist cyber attacks.
3
property regime
The loss of the international intellectual property regime as an
effective system for stimulating innovation and investment.
4
Massive digital
misinformation
Deliberately provocative, misleading or incomplete information
disseminates rapidly and extensively with dangerous
consequences.
5
Massive incident of data
fraud/theft
Criminal or wrongful exploitation of private data on an
unprecedented scale.
6
Mineral resource supply
vulnerability
Growing dependence of industries on minerals that are not widely
sourced with long extraction-to-market time lag for new sources.
7
Proliferation of orbital
debris
Rapidly accumulating debris in high-traffic geocentric orbits
jeopardizes critical satellite infrastructure.
8
Unforeseen
consequences of climate
change mitigation
Attempts at geoengineering or renewable energy
development result in new complex challenges.
9
Unforeseen
consequences of
nanotechnology
The manipulation of matter on an atomic and molecular level
raises concerns on nanomaterial toxicity.
10
Unforeseen
consequences of new
life science technologies
Advances in genetics and synthetic biology produce
unintended consequences, mishaps or are used as weapons.
10
2
8
6
9
4
7
1
5
3
3
2.5
2.5
3
3.5
4
Technological
1
2
6
10
8
4
3
9
5
3
7
2.5
2.5
3
3.5
4
Section 5
3.5
Section 4
4
Section 3
3.5
Section 2
1
NB: The scatter plots show the average value, across all responses, of the likelihood and impact of the 50 global risks, as measured on the horizontal and vertical axes, respectively.
Section 6
Global Risks 2013
47
Section 1
Section 2
Economic
Environmental
Geopolitical
Chronic fiscal
imbalances
Chronic labour
market
imbalances
Antibiotic-resistant Failure of
bacteria
climate change
adaptation
Critical fragile
states
Backlash against
Diffusion of
weapons of mass globalization
destruction
5
5
5
5
5
5
4
4
4
4
4
4
3
3
3
3
3
Impact
Figure 30: Distribution of Survey Responses
2
2
2
1
1
1
Likelihood 3
4
1
5
2
3
4
5
1
2
3
4
5
1
2
3
4
Societal
Technological
Food shortage
crises
Critical systems
failure
Cyber
attacks
5
5
5
5
4
4
4
4
3
3
3
3
3
2
2
2
2
2
2
1
1
1
1
1
5
1
2
3
4
1
5
2
3
4
1
5
2
3
4
5
1
2
3
4
5
1
1
2
3
4
1
5
2
3
4
Section 3
Extreme volatility
in energy and
agriculture prices
Hard landing of
an emerging
economy
Irremediable
pollution
Land and
waterway use
mismanagement
Entrenched
organized
crime
Failure of
diplomatic
conflict resolution
Ineffective illicit
drug policies
Mismanagement
of population
ageing
Failure of
intellectual
property regime
Massive digital
misinformation
5
5
5
5
5
5
5
5
5
5
4
4
4
4
4
4
4
4
4
4
3
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1
1
2
3
4
1
5
2
3
4
1
5
2
3
4
1
5
2
3
4
5
1
2
3
4
5
1
2
3
4
1
5
2
3
4
1
5
2
3
4
5
1
1
2
3
4
1
5
2
3
4
Major systemic
financial failure
Prolonged
infrastructure
neglect
Mismanaged
urbanization
Persistent
extreme
weather
Global
governance
failure
Militarization of
space
Rising rates of
chronic disease
Rising religious
fanaticism
Massive incident
of data
fraud/theft
Mineral resource
supply
vulnerability
5
5
5
5
5
5
5
5
5
5
4
4
4
4
4
4
4
4
4
4
3
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
1
5
2
3
4
1
5
2
3
4
5
1
2
3
4
5
5
5
1
1
2
3
4
5
1
2
3
4
5
Section 4
Recurring
liquidity crises
Severe income
disparity
Rising greenhouse Species
gas emissions
overexploitation
Pervasive
entrenched
corruption
Terrorism
Unmanaged
migration
Unsustainable
population
growth
Proliferation of
orbital debris
Unforeseen
consequences
of climate
change mitigation
5
5
5
5
5
5
5
5
5
5
4
4
4
4
4
4
4
4
4
4
3
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1
1
2
3
4
1
5
2
3
4
1
5
2
3
4
1
5
2
3
4
5
1
2
3
4
5
1
2
3
4
1
5
2
3
4
1
5
2
3
4
5
1
1
2
3
4
1
5
2
3
4
5
Section 5
Unforeseen
negative
consequences
of regulation
Unmanageable
inflation
or deflation
Unprecedented
geophysical
destruction
Vulnerability to
geomagnetic
storms
Unilateral
resource
nationalization
Widespread
illicit trade
Vulnerability to
pandemics
Water supply
crises
Unforeseen
Unforeseen
consequences of
consequences
new life science
of nanotechnology technologies
5
5
5
5
5
5
5
5
5
5
4
4
4
4
4
4
4
4
4
4
3
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
1
2
3
4
5
1
2
3
4
5
NB: These diagrams show how individual survey responses are distributed across the different possible combinations of likelihood and impact scores, as measured, respectively, on the horizontal and
vertical axes of the graphs. The darker the colour of the tile, the more often that particular combination was chosen by the experts who took the survey.
Compared with Last Year
Section 6
While there is some movement of individual dots, compared
with last year’s scatter plot, the general distribution of the
risks on the risk landscape is, perhaps unsurprisingly,
similar (see Figure 1). What is surprising, though, is that
respondents this year see risks as more likely and as having
a higher impact than respondents to the previous year’s
survey. The average likelihood score is 0.15 units higher (on
a scale from 1 to 5), and the average impact score is 0.13
units higher.
Part of the increase in impact (about a quarter of the
difference) can be explained by the fact that the average age
of the survey sample has decreased, and as shown below,
younger people tend to give higher answers when it comes
to assessing a risk’s impact. Nonetheless, even controlling
for age and other different characteristics of the sample, the
fact remains that the perceived likelihood and impact of
many of the risks have increased.
48
Global Risks 2013
Particularly interesting cases which had big increases in both
likelihood and impact scores are:
- the technological risks: unforeseen consequences of new life
science technologies and unforeseen consequences of
climate change mitigation;
- the economic risks: unforeseen negative consequences of
regulation, hard landing of an emerging economy and chronic
labour market imbalances;
- the two sides of global demographic imbalances:
unsustainable population growth and mismanagement of
population ageing; and
- the geopolitical risk: unilateral resource nationalization.
Only very few risks had their average scores decrease from last
year. On the likelihood scale, these include recurring liquidity
crises, vulnerability to geomagnetic storms and proliferation of
orbital debris. The only risk where there was a statistically
significant decrease in terms of its impact was food shortage
crises.
Section 1
By Organization
Survey respondents were asked to provide some information
about their background: their age, their gender, where they live,
for what kind of organization they work, and their subject-area
expertise. Using this demographic data the risks landscape was
cut up in different ways to see how different groups with specific
characteristics perceive global risks.
Similarly, it is possible to look at how the perceptions of people
who work at different types of organizations differ. This year, the
differences are less pronounced than last year. One striking
observation, though, is that for many risks, people working for
NGOs tend to assign higher scores than their peers from other
organizations. In particular, people from NGOs see many risks
as more likely than respondents from the government sector,
and they rate impacts more highly than those in the business
world (see Appendix 2 for more results).
Figure 32: Comparison between Organizational Affiliations
Academia
Business
4
4
The scatterplot for Latin America demonstrates that
respondents based in that region tend to assign a higher impact
to risks. For instance, they see the impact of ineffective illicit drug
policies as significantly higher than survey takers from other
regions. It is also interesting that average responses from
respondents based in Asia are clustered more densely together.
3.5
3.5
3
3
Figure 31: Comparison between Regions of Residence
4.5
4.5
4
4
3.5
3.5
3
3
Impact
4.5
Impact
4.5
Likelihood
3
3.5
4
4.5
Likelihood
Government
3.5
4
4.5
International Organization
4
4
3.5
3.5
3
3
Impact
4.5
Impact
Europe
4.5
3.5
4
Likelihood
4.5
4
4.5
Likelihood
3
3.5
4
4.5
3
3.5
4
4.5
3
3.5
4
4.5
Other
4.5
4.5
4
4
3.5
3.5
3
3
Middle East/North Africa
4.5
4
4
3.5
3.5
Impact
4.5
Impact
Latin America
3.5
NGO
Impact
3
3
Section 5
Impact
Likelihood
Likelihood
3
Section 4
Asia
Section 3
Figure 31, for instance, shows how respondents based in North
America tend to rate many risks as having a higher likelihood
than respondents in other regions. The dots are markedly further
to the right in the scatter plot, and for a large number of risks the
differences with other regions are statistically significant. These
include chronic fiscal imbalances, prolonged infrastructure
neglect, rising greenhouse gas emissions, diffusion of weapons
of mass destruction and cyber attacks (see Appendix 2 for
detailed results).
Likelihood
3.5
4
4.5
Likelihood
Impact
Impact
3
3
Section 6
3
Likelihood
3
3.5
4
Likelihood
4.5
North America
3
3.5
4
4.5
4
4.5
Sub-Saharan Africa
4.5
4
4
3.5
3.5
3
3
Impact
Impact
4.5
Likelihood
3
3.5
4
4.5
Likelihood
3
3.5
Section 2
By Region of Residence
Global Risks 2013
49
Section 1
By Age
The difference in perception between genders is very
pronounced, with women tending to rate both the likelihood and
impact of most risks higher than men. On average, the likelihood
rating is 0.11 units higher for women than for men, while the
difference between the impact scores is 0.21 units.xlviii
Figure 34 shows that respondents aged 40 or younger tend to
rate most risks as higher in impact than those over 40. There is no
risk where the older group’s impact scores are significantly higher.
For most individual risks, this difference was statistically
significant at the 5% level. There is only one risk, backlash
against globalization, which men rated as more likely than
women.
Section 3
The overall finding that men are generally less worried about
risks than women is in line with what has been observed in other
surveys about perceptions of other kinds of risk.1 The literature is
not in agreement as to the reasons for this result. Some believe
that women are generally more risk-averse than men, while
others argue the two genders perceive risks similarly but worry
about different risks, so it matters which risks surveys ask about.
Either explanation would have important implications for risk
managers and policy-makers wanting to use expert perceptions
to identify and assess global risks, and to make the most
informed decisions.
4.5
4
4
3.5
3
3
Figure 34: Comparison between Age Groups
Economic
Impact
3.5
Impact
Section 5
3
3.5
4
4.5
Likelihood
Geopolitical
3
3.5
4
4.5
Societal
4.5
4.5
4.5
4
4
3.5
3.5
3
3
Likelihood
4
3
3
Impact
3
3.5
4
4.5
3.5
4
4.5
Likelihood
Likelihood
3
3.5
4
4.5
4.5
4
4
3.5
3.5
3
3
Male respondents
3.5
4
4.5
3.5
4
4.5
Societal
4.5
Impact
Technological
4.5
3
Impact
Likelihood
Likelihood
3
3.5
4
4.5
Likelihood
3
Female respondents
Technological
4
4.5
espondents > 40 yrs
3.5
espondents ≤ 40 yrs
4
3
3.5
Likelihood
3
3.5
4
4.5
xlviii
3
Impact
Impact
Section 6
Impact
3.5
3
Geopolitical
4
3.5
Environmental
4.5
Impact
Section 4
Environmental
4.5
Likelihood
In contrast to the differences between the genders, the psychometric literature is less clear on the effect of age on risk perceptions. Some studies find that younger people generally worry less
about risks.2 However, most of these look at adolescents and
personal risks such as driving, drinking and smoking. It is not
surprising that this finding does not carry over to perceptions of
global risks among experts in their third or fourth decade of life.
On the other hand, studies that look at age differences in general,
not only at teenagers, support the finding from the present
survey that younger people generally perceive risks as higher.3
It is interesting that high-level decision-makers tend to be drawn
mostly from the group – older males – that the breakdowns by age
and gender indicate is least inclined to worry about global risks.
Figure 33: Comparison between Genders
Economic
For many risks, the younger experts also chose higher likelihood
scores. But there are a few exceptions, where respondents over
40 rated risks as more likely to occur in the next 10 years than
the respondents under 40: prolonged infrastructure neglect,
failure of climate change adaptation, rising greenhouse gas
emissions and diffusion of weapons of mass destruction.
Impact
Section 2
By Gender
Likelihood
3
3.5
Controlling for other characteristics of the sample, the respective differences would be
0.087 and 0.18 units.
50
Global Risks 2013
4
4.5
Section 1
4
4
3.5
3.5
3
3
Likelihood
4
4.5
Likelihood
3
3.5
4
4.5
3.5
4
4.5
Societal
Geopolitical
4.5
4
4
3.5
3.5
3
3
Impact
Impact
4.5
Likelihood
3
3.5
4
4.5
Likelihood
3
Technological
4.5
Experts in category
Non-experts in category
4
3.5
3
Likelihood
3
3.5
4
Section 5
Impact
These findings raise interesting questions. Are economists more
informed about economic issues than others, or are there
ideological differences at play? Are the technological specialists
more knowledgeable here, or does their excitement about new
technologies dampen their risk perceptions? And where experts
are more worried, does that mean that we should listen to them
more, or do they just feel more strongly about their issue without
knowing enough about other threats?
3.5
Section 4
On the other side of the equation, experts in economic issues
worry less about the impact and likelihood of severe income
disparity than non-experts. Similarly, technological experts
worry less than non-experts about the likelihood and impact of
unforeseen consequences of nanotechnology.
3
Section 3
Also there are a number of societal risks where specialists are
more alarmed than other respondents, such as rising rates of
chronic diseases, unsustainable population growth or unmanaged migration. In the economic category, this pattern holds
only for chronic fiscal imbalances. For most other risks in this
category, as well as in the geopolitical and in the technological
domains, there are few statistically significant differences.
Environmental
4.5
Impact
The differences between environmental experts and their peers
from other fields are striking – they assign higher impact and
likelihood scores to all 10 risks in the environmental category,
with most of these differences being statistically significant at the
5% level (see Appendix 2).
Economic
4.5
Section 2
Finally, it is possible to look at how subject expertise affects risk
perceptions. Respondents were asked to identify in which of the
five categories (which group the 50 risks) they consider themselves experts. While there is no generalization that can be
made about all risks, there are some interesting cases where
experts are more worried about risks.
Figure 35: Comparison between Experts
Impact
By Subject-matter Expertise
4.5
Section 6
Global Risks 2013
51
Section 1
Centres of Gravity
-
Section 2
For each of the five categories, survey-takers were asked to pick
a “Centre of Gravity” – the one risk that they thought is the
systemically most important one in that group. Due to their
influence on other risks, these are the risks to which leaders and
policy-makers should pay particularly close attention. Figure 36
shows how the answers to this question are distributed among
the different options. The top selected risks for Centres of
Gravity this year are:
major systemic financial failure (economic)
failure of climate change adaptation (environmental)
global governance failure (geopolitical)
water supply crises (societal)
critical systems failure (technological)
Three of the centres of gravity have changed from last year’s
report, in the economic, environmental and societal categories.
Figure 36: Centres of Gravity by Category
Economic risks
Section 3
Major systemic
financial failure
Environmental risks
2013
Failure of climate
change adaptation
22.7 %
26.4 %
2012
Severe income
disparity
20.8 %
19.9 %
Chronic fiscal
imbalances
3.5 %
Section 4
5.0 %
Hard landing of an
emerging economy
2.2 %
3.2 %
1.7 %
9.3 %
4.1 %
Section 5
10
20
8.9 %
6.2 %
13.6 %
3.9 %
3.4 %
3.5 %
Rising rates of
chronic disease
4.9 %
5.1 %
2.1 %
1.5 %
3.2 %
2.9 %
Unmanaged
migration
1.3 %
8.3 %
1.9 %
Ineffective illicit
drug policies
0.6 %
10
20
0.4 %
0
30
40.1 %
2013
2012
13.8 %
Section 6
12.0 %
10.6 %
9.5 %
4.7 %
3.8 %
1.6 %
8.1 %
3.4 %
3.0 %
of nanotechnology
1.7 %
0.8 %
1.0 %
0.6 %
0.8 %
0.6 %
0
6.8 %
property regime
2.6 %
7.8 %
4.9 %
Massive incident of
data fraud or theft
1.9 %
9.8 %
7.2 %
Unforeseen consequences of
new life science technologies
5.3 %
Entrenched
organized crime
12.8 %
8.7 %
Massive digital
misinformation
14.7 %
Unilateral resource
nationalization
4.1 %
Mineral resource
11.7 %
Diffusion of weapons
of mass destruction
18.1 %
15.1 %
8.5 %
10
Percent of responses
20
30
44.8 %
20.9 %
Cyber attacks
12.8 %
Terrorism
20
21.7 %
14.1 %
conflict resolution
10
Technological risks
29.2 %
2013
2012
corruption
Global Risks 2013
13.9 %
9.1 %
Global governance
failure
52
11.9 %
Vulnerability to
pandemics
3.8 %
Geopolitical risks
12.3 %
10.9 %
Backlash against
globalization
5.8 %
0
30
9.4 %
Mismanagement of
population ageing
13.2 %
Vulnerability to
geomagnetic
storms
23.9 %
14.9 %
Rising religious
fanaticism
7.0 %
Species
overexploitation
2.8 %
0
9.5 %
Unprecedented
geophysical
destruction
4.2 %
2.6 %
17.1 %
Food shortage
crises
9.0 %
Antibiotic-resistant
bacteria
4.4 %
Unmanageable
inflation or
deflation
Prolonged
infrastructure
neglect
Unforeseen negative
consequences
of requlations
14.9 %
Irremediable
pollution
1.7 %
Recurring
liquidity crises
31.6 %
Land and
waterway use
mismanagement
6.8 %
Chronic labour
market imbalances
13.0 %
Unsustainable
population growth
17.2 %
Persistent
extreme weather
10.3 %
7.6 %
22.4 %
2013
2012
Water supply crises
22.0 %
Mismanaged
urbanization
32.0 %
Extreme volatility
in energy and
agriculture prices
26.2 %
2013
2012
Rising greenhouse
gas emissions
18.1 %
Societal risks
30
40
0.4 %
0
10
20
30
40
Section 1
Figure 37: The Risk Interconnection Map 2013
Cyber attacks
Section 2
Terrorism
Widespread
illicit trade
Unforeseen negative
Mineral resource
mismanagement
Section 3
Ineffective
illicit drug
policies
Water supply crises
Persistent extreme
weather
Chronic fiscal
imbalances
Unmanaged migration
Rising rates of
chronic disease
Unprecedented
geophysical
destruction
Section 4
Antibiotic
resistant
bacteria
Interconnections
Figure 39: Top 10 Most Connected Risks
Finally, the survey asked respondents to choose pairs of risks
which they think are strongly interconnected.xlix They were asked to
pick a minimum of three and maximum of ten such connections.
529 different connections were identified by survey respondents
out of the theoretical maximum of 1,225 combinations possible.
The top selected combinations are shown in Figure 38.
41
40
33
33
32
Extreme volativity in energy & agriculture prices
30
30
30
Section 6
It is also interesting to see which are the most connected risks
(see Figure 39) and where the five centres of gravity are located
in the network (see Figure 40).
44
Section 5
Putting together all chosen paired connections from all
respondents leads to the network diagram presented in Figure 37
– the Risk Interconnection Map. The diagram is constructed so
that more connected risks are closer to the centre, while weakly
connected risks are further out. The strength of the line depends
on how many people had selected that particular combination.
29
0
10
20
30
40
50
Number of connections
Figure 38: Top Five Most Selected Connections
Box 8: The Global Risks 2013 Data Explorer
and Terrorism
90
and Backlash against globalization
79
and Major systemic financial failure
72
Extreme volativity in energy & agriculture prices
and Food shortage crises
68
and Failure of climate change adaptation
59
0
20
40
60
80
100
Number of responses
Readers are invited to visit the Data Explorer on the
accompanying website to the Global Risks 2013 report. There it
is possible to interact with the Global Risks Landscape, the
Global Interconnection Map, and the data from the two new
survey questions on national resilience. The data explorer is also
an entry point to other relevant Forum reports, videos, and blog
posts – including the “What-If? Interview” seriesl by the Risk
Response Network – and many other types of resources around
each of the 50 global risks covered in this report.
xlix
When two risks are connected, it simply means that respondents believe that there is some
sort of correlation between the two. Causal direction cannot be deduced.
Visit the Global Risks Data Explorer: http://www.weforum.org/
globalrisks2013/dataexplorer.
Global Risks 2013
53
Section 1
Figure 40: Centres of Gravity and their Connections
Cyber attacks
Section 2
Terrorism
Terrorism
Failure of climate change
adaptation
Globalgovernance
Global
governance
failurefailure
property regime
corruption
Mineral resource
Land and waterway use mismanagement
Unprecedented
geophysical
destruction
Water supply crises
Unmanaged migration
Section 3
Mismanaged
urbanization
Antibiotic resistant bacteria
Cyber attacks
Terrorism
Critical fragile
states
Section 4
Global governance
failure
property regime
corruption
Entrenched organized
crime
corruption
Mineral resource
Water supply crises
Chronic fiscal
imbalances
Mismanaged
urbanization
Unmanaged
migration
Unmanaged migration
Section 5
Cyber attacks
Terrorism
Widespread
Hard landing of an emerging
illicit trade
economy
corruption
Global
governance
failure
property regime
Extreme volatility
in energy and
agriculture prices
Section 6
Mineral resource
Water supply crises
Persistent
Unprecedented geophysical
extreme
destruction
weather
Mismanaged
urbanization
Unmanaged
migration
Irremediable l pollution
Rising rates of
chronic disease
Land and waterway
use mismanagement
Chronic fiscal
imbalances
1.
Finucane, M. L., Slovic, P., Mertz, C. K., & Flynn, J. Gender, Race, and Perceived Risk: the ’White
Male’ Effect. In Health, Risk and Society, 2000, 2:159-172; Gustafson, P.E. Gender Differences in
Risk Perception: Theoretical and Methodological Perspectives. In Risk Analysis, 1998,
18:805-811; and Harris, C. R., Jenkins, M., & Glaser, D. Gender Differences in Risk Assessment:
Why do Women Take Fewer Risks than Men. In Judgment and Decision Making, 2006, 1:48-63.
2.
Deery, H.A. Hazard and Risk Perception among Young Novice Drivers. In Journal of Safety
Research, 1999, 30:225-236; and Jonah, B.A., & Dawson, N.E. Youth and Risk: Age Differences
in Risky Driving, Risk Perception, and Risk Utility. In Alcohol, Drugs & Driving, 1987, 3:13-29.
3.
Savage, I. Demographic Influences on Risk Perceptions. In Risk Analysis, 1993, 13:413-420.
l
54
The “What If?” series seeks to generate new insights around risks that global experts from
academia, business, government and civil society believe to be underappreciated. By
exploring hypothetical scenarios in detail, leaders are able to uncover complex
interconnectivity between systems and issues and by exploring global risks as scenarios,
experts have the space to surface sensitive issues. The What-If series is a platform for
leaders to assess their resilience against such risks and even seize opportunities they may
present.
Global Risks 2013
Mismanaged
urbanization
Section 1
X Factors
Section 2
The threat of climate change is well known. But have we passed
the point of no return? What if we have already triggered a
runaway chain reaction that is in the process of rapidly tipping
Earth’s atmosphere into an inhospitable state?
The natural greenhouse effect is a prerequisite for life on our
planet. Without it, Earth’s global average surface temperature
would be far below zero. But our planet’s climate is a volatile
beast. Small fluctuations in the Earth’s orbit around the sun can
exert a major influence on our climate. So can the varying
concentration in Earth’s atmosphere of heat-trapping molecules
such as carbon dioxide, to which we have been adding through
greenhouse gas emissions.
Section 4
How pronounced and how fast the warming will be (and how it
will affect rainfall and storminess where you live) is hard to say as
even the most sophisticated computer models cannot capture
all the factors involved in a system as complex as the Earth. But
it could be more dramatic and difficult to adapt to than most
scientists predict, because of the natural ‘feedbacks’ in the
system, linked to processes in the oceans1 and on land2. They
have the potential of amplifying climate change to a point of
fundamentally disrupting the global system. The much-debated
questions are where these tipping points lie, how soon they
might be reached, whether they can be predicted – and what
will happen when they are crossed.3
Section 5
In a world of many uncertainties we are
constantly on the search to identify “X
factors” – emerging concerns of possible
future importance and with unknown
consequences. Looking forward and
identifying emerging issues will help us to
anticipate future challenges and adopt a
more proactive approach, rather than being
caught by surprise and forced into a fully
reactive mode.
Runaway Climate Change
Section 3
In this section, developed in collaboration
with Nature, a leading science journal, the
Risk Response Network asks readers to
look beyond our high-risk concerns of the
moment to consider a set of five X factors
and reflect on what countries or companies
should be doing to anticipate them.
Section 6
X factors are serious issues, grounded in the
latest scientific findings, but somewhat
remote from what are generally seen as
more immediate concerns such as failed
states, extreme weather events, famine,
macroeconomic instability or armed conflict.
They capture broad and vaguely understood
issues that could be hatching grounds for
potential future risks (or opportunities).
Global Risks 2013
55
Section 1
Section 2
The perhaps best-known positive feedback mechanism is the
so-called ice-albedo feedback. In a warmer world there will be less
snow and sea ice. Their melting reveals the darker land and water
surfaces below, which absorb more solar heat. More absorption
then causes yet more melting and warming, and so forth, in a
self-reinforcing feedback loop. The unprecedented thawing of 97%
of Greenland’s surface ice in July 2012, for example, has led to a
darkening of Greenland’s ice cap, meaning it will begin to absorb
higher levels of solar energy and melt faster still.
Section 3
Melting of the complete Arctic summer sea ice – the Arctic is
expected to be seasonally ice-free by around 2040 – could
probably be reversed on human timescales if greenhouse gases
are reduced and temperature drops. But if the several kilometrethick ice sheets that cover Greenland and Antarctica dwindle,
they may not so easily reappear in a cooler world. New ice would
have to form at low elevations, where temperatures are higher.
Permafrost melting, land use and vegetation changes, and the
effects of changing cloud cover provide for other major feedback
mechanisms. Some scientists suspect that by 2040 up to 63
billion extra tonnes of carbon – and up to 380 billion tonnes by
2100 – might be released by the thaw and degradation of
permafrost soil alone.4
Section 4
Finally, there is the potentially huge feedback effect of water
vapour, a natural greenhouse gas in itself. A warmer atmosphere
can hold more water. As the average air temperature soars in
response to our burning of fossil fuels, evaporation and
atmospheric concentration of water vapour will increase, further
intensifying the greenhouse effect. On Venus, this probably caused
a runaway greenhouse effect, which boiled away the oceans that
may have existed in the planet’s early history.
Section 5
Luckily, man-made climate warming has virtually no chance of
producing a runaway greenhouse effect analogous to Venus.
Even so, scientists with the Intergovernmental Panel on Climate
Change (IPCC) reckon that the water vapour feedback on Earth
could be strong enough to double the greenhouse effect due to
the added carbon dioxide alone.
While climate change debates of the past decade centred around
whether or not mankind could be responsible at all for altering a
system as great at Earth’s climate, we may be rapidly moving into
forced discussions on how best to strengthen mankind’s resilience
and adaptive capacity to cope as Earth’s climate auto-pilot
mercilessly hurtles us toward a new and unknown equilibrium.
Enhancement could come from hardware as well as drugs. A
handful of studies in people show that electrical stimulation –
either directly via implanted electrodes or through the scalp with
transcranial magnetic stimulation (TMS) – can boost memory.
Cochlear implants are already standard treatment for the deaf,
and motor implants for controlling neural prosthetics and
devices are developing fast and seem likely to become available
more widely in coming years. Retinal implants for the blind are a
bit further behind, but the field is booming and it seems likely
that they will be worked out soon.
The best interfaces still rely on invasive brain electrodes
(noninvasive techniques do work, but are slow and inefficient),
which is the major barrier to these being adopted by healthy
people. But it seems conceivable that within 10 years we will
either have a new method for recording brain activity or the
noninvasive signals will be decoded more efficiently. Direct brain
interfaces of devices and sensors within our lifetimes is not out
of the question, opening a new realm of enhanced neurobiology
for those who can afford it.
Section 6
This will pose ethical issues in many walks of life akin to those
which surround “doping” in the world of professional sports. Will
we accept the idea that significant cognitive enhancement
should be available to purchase on the open market? Or will
there be, as there now is with performance enhancers in
competitive sports, a push for legislation to maintain a more level
playing field?
Significant Cognitive Enhancement
Once the preserve of science fiction, superhuman abilities are
fast approaching the horizon of plausibility. Will it be ethically
accepted for the world to divide into the cognitively-enhanced
and unenhanced? What might be the military implications?
Scientists are working hard to develop the medicines and
therapies needed to heal the brain of mental illnesses such as
Alzheimers and schizophrenia. Although progress has been
slow, it is conceivable that in the not-too-distant future,
researchers will identify compounds that improve on existing
cognitive pharmaceutical enhancers (e.g. Ritalin, modafinil).
Although they will be prescribed for significant neurological
disease, effective new compounds which appear to enhance
intelligence or cognition are sure to be used off-label by healthy
people looking for an edge at work or school.
56
Global Risks 2013
There is, in addition, a significant risk of cognitive enhancement
going very wrong. Cognitive enhancement pharmaceuticals work
by targeting particular neurotransmitter systems, and therefore will
most likely have wide-ranging action. There is a significant
possibility of unintended effects on other systems – for example,
drugs to enhance learning might lead to a greater willingness to
take risks; drugs to enhance working memory might lead to
increased impulsive behavior. Recent research suggests that, in
addition to boosting memory, TMS could be used to manipulate a
person’s beliefs of right versus wrong or to suspend moral
judgement altogether. It could also be used to “erase” memory and
deliberately cause permanent brain damage without the use of
invasive procedure or blunt force trauma.
Section 1
Such advancements could have profound impacts in 20 to 50
years on societal norms affecting how we approach issues
incuding education and training, disparity between groups in
society, informed consent and exploitation, and international
laws on warfare.
Rogue Deployment of Geoengineering
The problem is that the only way to truly test solar radiation
management is at scale. This potentially conflates large-scale
research with deployment, thereby giving rogue nations political
cover under the guise of science. Much research has gone into
whether a programme could be targeted at the Arctic, for
instance, where the impacts of global warming are being felt the
most, but some researchers suggest that the impacts could
quickly migrate from the Arctic to other regions. Many say that a
true test of solar radiation management would have to be global.
Due to such complexities, most of the science to date has been
conducted via computer modelling, although scientists are
looking for ways to test these ideas with local experiments. But
overall, despite calls for more coordinated government science
programmes, the funding landscape for this kind of science
remains spotty.
Section 5
Most research has focused on sulphur injection via aircraft.
Recent studies suggest that a small fleet of aircraft could inject a
million tonnes of sulphur compounds into the stratosphere –
enough to offset roughly half of the global warming experienced
to date – for US$1-2 billion annually.li In theory, the technology
would be tantamount to a planetary thermostat, giving humans
direct control over global temperature. The direct impact of
dimming the sun would be felt within weeks to months.
But this has led some geoengineering analysts to begin thinking
about a corollary scenario, in which a country or small group of
countries precipitates an international crisis by moving ahead
with deployment or large-scale research independent of the
global community. The global climate could, in effect, be hijacked
by a rogue country or even a wealthy individual, with unpredictable costs to agriculture, infrastructure and global stability.
Section 4
Geoengineering can refer to many things, but it is most often
associated with a scientific field that has come to be known as
“solar radiation management”. The basic idea is that small particles
could be injected high into the stratosphere to block some of the
incoming solar energy and reflect it back into space, much as
severe volcanic eruptions have done in the past. In stark contrast
to decades of technological evolution and political disputes about
overhauling energy infrastructure to reduce greenhouse emissions,
solar radiation management would act quickly and would be
cheap to implement – though side-effects may make it a very
expensive option.
Nobody envisions deployment of solar radiation management
anytime soon, given the difficulties in resolving a suite of
governance issues (evidenced by the fact that even the
relatively simple SPICElii experiment in the UK foundered in the
midst of controversy).6 Beginning with Britain’s Royal Society,
many academic and policy bodies have called for cautious
research as well as broader conversation about the implications
of such technologies.
The individual hoped to net lucrative carbon credits, but his
actions may have been in violation of two international
agreements.7 Observers are concerned that this may be a sign
of what is to come.8
The most detailed cost and engineering analysis was commissioned by David Keith,
currently at Harvard University, and conducted by Aurora Flight Sciences. That analysis,
formally completed in July 2011, suggests that a small fleet of aircraft could inject a million
tonnes of sulphur into the stratosphere – enough to offset roughly half of the global warming
experienced to date – for US$ 1-2 billion annually.
lii
Stratospheric Particle Injection for Climate Engineering (SPICE) is a UK government-funded
geoengineering research project that aims to assess the feasibility of injecting particles into
the stratosphere from a tethered balloon for the purposes of solar radiation management.
Global Risks 2013
57
Section 6
This leaves a gap for unregulated experimentation by “rogue”
parties. For example, an island state threatened with rising sea
levels may decide they have nothing to lose, or a well funded
individual with good intentions may take matters into their own
hands. There are signs that this is already starting to occur. In
July 2012 an American businessman sparked controversy
when he dumped around 100 tonnes of iron sulphate into the
Pacific Ocean off the west coast of Canada in a scheme to
spawn an artificial plankton bloom. The plankton absorb
carbon dioxide and may then sink to the ocean bed, removing
the carbon – another type of geoengineering, known as ocean
fertilisation. Satellite images confirm that his actions succeeded
in produce an artificial plankton bloom as large as 10,000
square kilometres.
li
Section 3
In response to growing concerns about climate change, scientists
are exploring ways in which they could, with international
agreement, manipulate the earth’s climate. But what if this
technology were to be hijacked by a rogue state or individual?
However, a long series of ethical, legal and scientific questions
quickly arises about countless knock-on effects that might be
much more difficult to assess. The problem is that incoming
solar radiation drives the entire climate system, so reducing
sunlight would fundamentally alter the way energy and water
moves around the planet. Almost any change in weather and
climate patterns is likely to create winners and losers, but
determining causation and quantifying impacts on any given
region or country would be a massive challenge.
Section 2
Both the intended and unintended effects of such new
technologies would open whole new categories of potential
“dual-use” dilemmas. (Dual-use describes technologies which
can be used for good as well as for substantial harm.) It is not
difficult to see how such drugs could find applications in armed
forces and law enforcement contexts, or conversely by criminal
organizations and terrorist groups. They could spark an arms
race in the neural “enhancement” of combat troops.5
Section 1
Costs of Living Longer
Section 2
We are getting better at keeping people alive for longer. Are we
setting up a future society struggling to cope with a mass of
arthritic, demented and, above all, expensive, elderly who are in
need of long term care and palliative solutions?
The blessings of 20th-century medicine look set to explode with
the deciphering of the genome and attendant advances. It is
hoped that big inroads against common banes such as heart
disease, cancer and stroke, may be in the offing. Consider the
impact on society of a growing number of elderly infirm who are
protected from the most common causes of death today, but
with an ever deteriorating quality of life as other ailments that do
not kill, but seriously disable, start to dominate.
Section 3
Current trends are already setting the stage for such a future
scenario in the West. Already, the demographics of the Baby
Boom are working against us: conservative estimates say that
the number of Americans afflicted with Alzheimer’s disease will
at least double, to 11 million, by mid-century.9 Similar rises are
projected for many countries, with the global population of the
demented expected to double every 20 years until it exceeds
115 million in 2050.10 A key driver will be increasing elderly
populations and potentially declining fertility rates in low and
middle income countries.
Section 4
The looming expense of caring for these masses is mind
boggling, especially in high-income countries. The UK, for
instance, spends nearly as much each year caring for the
demented (£23 billion) as it does on stroke (£5 billion), heart
disease (£8 billion) and cancer (£12 billion) combined.11 And the
numbers afflicted with all of these maladies are only going to
grow.
Section 5
Consider Medicare, the US health programme for the elderly.
Assuming no policy changes – for instance, no increase in the
age of eligibility – the programme’s outlays are expected to
exceed its taxpayer-funded income by more than US $24 trillon
over the next 75 years.12,liii The spending trend is not limited to
government support, either. In the US, the cumulative total of
public and private consumption by the elderly has ballooned in
the last half century. The burden is accentuated in rapidly-aging
countries like Germany, where the ratio of effective producers
per consumer is projected to decline nearly 25% by 2030.13
Section 6
liii
58
See page 46 and 47 under “financial statements” at http://www.gao.gov/financial/
fy2011/11stmt.pdf. Add total liabilities for Medicare parts A, B and D together to get US$
24.5 trillion. (3,252 billion + 18,854 billion + 7,466 billion)
Global Risks 2013
Life expectancy has increased steadily in every decade since
1840, but these gains do not necessarily portend better health in
later life.14 Thus, a new wave of disabled seniors may be on the
way. The proportion of Americans aged 50 to 64 who reported
needing help with personal care activities – things like getting
into and out of bed, and climbing ten steps – increased
significantly in the decade ending in 2007. Arthritis was the top
cause, and diabetes played a prominent and growing role.15
Are there fixes that can avert the coming storm? There are
well-known but difficult-to-implement preventive measures that
could help us live both longer and better quality of lives:
paramount among them is exercise, with its near-universal
benefits for our physiologies and for warding off pathology.16
Obvious ways to mitigate cost implications would include raising
the eligibility ages for the programmes that support the elderly
from the public purse – retirement income, social support
services or reduced-cost health care – and raising the retirement
age, requiring older adults to be productive economically for
longer. One recent analysis, using a “delayed aging” model,
found that hundreds of billions of dollars in increased costs to
the US Medicare and Social Security programmes could be
entirely offset by raising the eligibility ages for Medicare and
Social Security by a few years (from 65 to 68, and from 67 to
68).17
However, raising eligibility ages for public services is not a
panacea, in part because financial costs are not the only
challenge. The impacts of aging populations will be felt
throughout society, from changing best practices in urban
planning to impacting social norms around care-giving. More
research is needed to turn chronic conditions to acute
conditions (i.e. by developing curative treatments), and find
solutions that increase the capacity of all citizens to manage
chronic conditions and to create wealth at the same time.
Discovery of Alien Life
Given the pace of space exploration, it is increasingly
conceivable that we may discover the existence of alien life or
other planets that could support human life. What would be the
effects on science funding flows and humanity’s self-image?It
was only in 1995 that we first found evidence that other stars also
have planets orbiting them. Now thousands of “exoplanets”
revolving around distant stars have been detected. NASA’s Kepler
mission to identify Earth-sized planets located in the “Goldilocks
Zone” (not too hot, nor too cold) of Sun-like stars, has only been
operating for 3 years and has already turned up thousands of
candidates, including one the size of Earth. The fact that Kepler
has found so many planet candidates in such a tiny fraction of the
sky suggests there are countless Earth-like planets orbiting
sun-like stars in our galaxy. In 10 years’ time we may have
evidence not only that Earth is not unique, but that life exists
elsewhere in the universe.
Suppose the astronomers who study exoplanets one day find
chemical signs of life – for example, a spectrum showing the
presence of oxygen, a highly reactive element that would quickly
disappear from Earth’s atmosphere if it were not being replenished
by plants. Money might well start flowing for new telescopes to
study these living worlds in detail, both from the ground and from
space. New funding and new brain power might be attracted to
the challenges of human space flight and the technologies
necessary for humanity, or its A.I. emissaries, to survive an
inter-stellar crossing.
Section 1
Schmittner, A. & Galbraith, E.D. Glacial Greenhouse-gas Fluctuations Controlled by Ocean
Circulation Changes. In Nature, 2008, 456:373-6.
2.
Arneth, A., Harrison, S. P., Zaehle, S., et al. Terrestrial Biogeochemical Feedbacks in the Climate
System. In Nature Geoscience, 2010, 3:525-532.
3.
Lenton, T. M., Held, H., Kriegler, E., et al. Tipping Elements in the Earth’s Climate System. In
Proceedings of the National Academy of Sciences, 2008, 105:1786-93.
4.
Schuur, E.A. & Abbott, B. Climate Change: High Risk of Permafrost Thaw. In Nature, 2011,
480:32-3.
5.
Tennison, M.N. & Moreno, J.D. Neuroscience, Ethics, and National Security: The State of the Art.
In PLoS Biology, 2012, 10:e1001289.
6.
Cressey, D. Cancelled Project Spurs Debate over Geoengineering Patents. In Nature, 2012,
485:429.
7.
“Decision Adopted by the Conference of the Parties to the Convention On Biological Diversity at
its Tenth Meeting: X/33 Biodiversity and climate change”. UNEP, Convention on Biological
Diversity, http://www.cbd.int/climate/doc/cop-10-dec-33-en.pdf, 2010; and Lukacs, M. World’s
Biggest Geoengineering Experiment ‘Violates’ UN Rules. In The Guardian, 2012.
8.
Macnaghten, P. & Owen, R. Environmental Science: Good Governance for Geoengineering. In
Nature, 2011, 479:293.
9.
“Recommendations of the Public Members of the Advisory Council on Alzheimer’s Research,
Care, and Services”. U.S. Department of Health and Human Services, Advisory Council on
Alzheimer’s Research, http://aspe.hhs.gov/daltcp/napa/AdvCounRec.pdf, 2012.
10.
Dementia: A Public Health Priority. 2012. Geneva: World Health Organization;
11.
Ibid.; and Luengo-Fernandez, R., Leal, J. & Gray, A.M. UK Research Expenditure on Dementia,
Heart Disease, Stroke and Cancer: Are Levels of Spending Related to Disease Burden? In
European Journal of Neurology, 2012, 19:149-54.
12.
“Financial Statements of the United States Government for the Years Ended September 30,
2011, and 2010”. Financial Management Services, http://www.fms.treas.gov/fr/11frusg/11stmt.
pdf, 2011.
13.
Lee, R. & Mason, M. “Population Aging and the Welfare State in Europe”. Global Trends 2030,
http://gt2030.com/2012/08/01/population-aging-and-the-welfare-state-in-europe/, 2012.
14.
Sciences, 2011, 66B:75-86.
15.
Martin, L. G., Freedman, V. A., Schoeni, R. F., et al. Trends in Disability and Related Chronic
Conditions among People Ages Fifty to Sixty-four. In Health Affairs (Millwood), 2010, 29:725-31.
16.
Tatar, M., Bartke, A. & Antebi, A. The Endocrine Regulation of Aging by Insulin-like Signals. In
Science, 2003, 299:1346-51.
17.
Goldman, D. Personal Communication. In Nature, Editor 2012.
Section 4
The fledgling space economy had a big year in 2012, which saw the
birth of space trucking when the first commercially built and
operated spacecraft successfully rendezvoused with the
International Space Station, and a host of celebrity billionaires
declared intentions to make asteroid mining a reality. Discovery of an
Earth 2.0 or life beyond our planet might inspire new generations of
space entrepreneurs to also take on the challenge of taking human
exploration of the galaxy from the realm of fiction to fact.
1.
Section 3
The discovery’s largest near-term impact would likely be on
science itself. Suppose observations point to a potential future
home for mankind around another star, or the existence of life in
our solar system – in the Martian poles, or in the subsurface
oceans of Jupiter’s frozen moon Europa, or even in the
hydrocarbon lakes of Saturn’s moon Titan. Scientists will
immediately start pushing for robotic and even human missions to
study the life forms in situ – and funding agencies, caught up in the
excitement, might be willing to listen.
References
Section 2
The discovery would certainly be one of the biggest news stories
of the year, and interest would be intense. But it would not change
the world immediately. Alien life has been ‘discovered’ before, after
all. Around the turn of the 20th century, the US astronomer Percival
Lowell convinced a great many people (including himself) that
Mars was crisscrossed by a vast system of canals built by a dying
civilization. But the belief that humankind was not alone did not do
much to usher in an era of brotherhood and earthly harmony, nor
did it stop the outbreak of World War I in 1914.
Section 5
Over the long term the psychological and philosophical implications of the discovery could be profound. If lifeforms (even fossilized
lifeforms) are found in our own solar system, for example, it will tell
us that the origin of life is ‘easy’ – that anyplace in the universe life
can emerge, it will emerge. It will suggest that life is as natural and
as ubiquitous a part of the universe as stars and galaxies are. The
discovery of even simple life would fuel speculation about the
existence of other intelligent beings and challenge many assumptions which underpin human philosophy and religion.
Through basic education and awareness campaigns the general
public can achieve a higher science and space literacy and
cognitive resilience that would prepare them and prevent
undesired social consequences of such a profound discovery and
paradigm shift concerning mankind’s position in the universe.
Section 6
Global Risks 2013
59
Section 1
Conclusion
Section 2
The eighth edition of the Global Risks report has sought to
highlight the theme of resilience in the context of systems
thinking. Exogenous in nature, global risks cannot be adequately
managed or mitigated by any single organisation. We have
introduced the conceptual framework of Professors Kaplan and
Mikes1, contrasting “external” risks such as global risks with
“preventable” and “strategic” risks, to assist clarity of thought
about how global risks should be approached. Whenever it is
difficult to predict how and when a risk will manifest, nurturing
resilience is the preferred approach.
Section 3
Section 4
Throughout this report we have sought to frame risks in a
systems context given its nature of interdependencies and to
assist clarity of thinking about the best ways to build resilience.
Our three risk cases have discussed what happens when two
major systems are stressed simultaneously (Testing Economic
and Environmental Resilience); when a seemingly more minor
system punches above its weight (Digital Wildfires in a
Hyperconnected World); and when we become complacent in
the continued ability of a system to stay one step ahead of a
changing problem (The Dangers of Hubris on Human Health). In
the Special Report, we explored the thinking of systems
theorists about how to build resilient systems, describing how
five components – redundancy, robustness, resourcefulness,
response and recovery – can be applied to selected national
subsystems.
Section 5
As ever, this report forms the starting point of dialogue which will
continue throughout the year, through a number of channels: our
dedicated virtual platform for members of the Risk Response
Network’s trusted community; the Resilience Practices
Exchange; workshops with our report partners and their
stakeholders; regional events around the world; and, of course,
our Annual Meetings in the People’s Republic of China and in
Davos-Klosters, Switzerland, where the theme for 2013 is
resilient dynamism.
Specifically, in 2013 we will take forward the task of building a
trusted network of risk experts to help global leaders map,
mitigate, monitor and enhance resilience to global risks. And we
will work to develop and refine the National Resilience Rating
proposed in the Special Report. The hyperconnected nature of
the modern world makes it increasingly urgent to understand
how best to build resilience in the face of global risks.
Section 6
More information on these initiatives and other World Economic
Forum activities on global risks can be found at
www.weforum.org/risk. You can contact us at rrn@weforum.org
and stay connected by following us at @WEFRisk.
1
60
Kaplan, R.S. & Mikes, A. Managing Risks: A New Framework. In Harvard Business Review,
2012.
Global Risks 2013
Section 1
Type of Organization
International Organizations - 95 (7.7%)
Government - 100 (8.1%)
Other - 102 (8.3%)
Section 2
Appendix 1
The Survey
Figure 41: Breakdown of Survey Sample
Business - 519 (42.1%)
NGO - 198 (16.0%)
Academia - 220 (17.8%)
Region of Residence
Sub-Saharan Africa - 72 (5.8%)
Middle East/North Africa - 77 (6.2%)
Europe - 368 (29.8%)
Latin America - 116 (9.4%)
Asia - 274 (22.2%)
North America - 327 (26.5%)
Region of Expertise
Middle East/North Africa - 83 (6.7%)
Sub-Saharan Africa - 95 (7.7%)
The survey sample includes experts in a range of subjects.
Approximately 29% of respondents are female, and the average
age of survey respondents is 43. With the inclusion of the new
Global Shapers Community – a group of young leaders between
20 and 30 years oldliv – the range of age groups covered by the
survey is wider than it was last year.
Europe - 316 (25.6%)
Latin America - 132 (10.7%)
North America - 302 (24.5%)
Asia - 306 (24.8%)
Age
19-20
3
20-30
294
30-40
249
40-50
288
50-60
216
60-70
125
70-80
21
200
300
Section 6
100
The survey sample closely resembles the targeted survey
population as described above. The distribution of people
across regions and types of organizations is nearly identical; the
average age is slightly lower (by two years) and the proportion of
women is slightly higher (by 3 percentage points). It is important
to note that the data is not intended to be representative of wider
populations than this specific survey population.
Section 5
In the 2012 survey, in addition to greater diversity of affiliation,
respondents also come from more diverse regions of the world
(see Figure 41). They indicated 101 different countries as their
country of residence, and self-identified expertise on 115
different countries. This has increased compared to 2011, where
only 69 countries were chosen as country of residence. There
was an increase in representation from Asia, Latin America,
Middle East/North Africa and Sub-Saharan Africa with a larger
number of responses from Japan, China and India for Asia;
Costa Rica, Mexico and Brazil for Latin America; and Nigeria
and South Africa for Sub-Saharan Africa.
Section 4
The Global Risks Perception Survey was carried out as an online
survey during September 2012. The purpose of the survey is to
sample the views of the World Economic Forum’s communities,
which comprise of top experts and high-level leaders from
business, academia, NGOs, international organizations, the
public sector and civil society. Over 6,000 invitations were sent
out and 1,234 respondents returned the questionnaire with
usable information; 1,006 of these were complete responses –
compared to 469 in 2011.
Section 3
Survey Sample
Number of responses
Area of Expertise
Economic Issues
612
Societal Issues
569
Geopolitical Issues
372
Technological Issues
327
Environmental Issues
234
100
200
300
400
500
600
Number of responses
NB: Multiple selections were possible for the question on expertise
liv
See http://www.weforum.org/globalshapers for more information.
Global Risks 2013
61
Section 1
The Questionnaire
The questionnaire consisted of three different sections with the
following questions:
Section 2
Section 1 covered the above-mentioned demographic
information.
In Section 2, respondents were asked to assess each of the 50
global risks covered in this report, by stating how they would
rate, on a scale from 1 to 5, the likelihood that the risk is to occur
over the next 10 years, and if it were to occur, the impact it would
have on the world.
Section 3
In addition, a new question was introduced this year to think
about the country that they had identified in Section 1 as the
country about which they have most expertise, and rate the
ability of that country to adapt and/or recover from the impact of
each of the 50 global risks.
The answer options to these three questions were presented as
Likert-type scales, where the respondent, using a slider on the
screen, was able to select a value ranging from 1 (low) to 5 (high)
as well as the midpoints between these integers.
Section 4
For each category of risks – economic, environmental,
geopolitical, societal and technological – the last question in
Section 2 asks survey respondents to select what they thought
would be the “Centre of Gravity”, i.e. the single most important
risk from a systemic perspective. They could choose from the 10
risks in each category via a drop-down menu.
Finally, in Section 3, respondents were asked to identify strong
connections between pairs of risks. They had the opportunity to
select at least three and up to 10 combinations, by dragging tiles
into paired boxes from the pool of 50 risks.
Section 5
Margin of Errors
Based on the spread of the answers as well as the survey
sample size, one can calculate the margin of error, based on a
95% confidence level.
For the global likelihood and global impact questions (Figures 1,
2, 29, 30), which were answered by all 1,234 respondents, the
maximumlv margin of error is 0.07 units.
Section 6
For the question on the Centres of Gravity (Figure 36), the
maximumlvi margin of error is 2.7 percentage points.
For the question on country recovery and adaptability, the
margin of error is heavily dependent on how many people
assessed the country in the question (as explained above,
survey respondents could choose which country to assess). The
tables in Appendix 3 detail the values.
Appendix 2
Likelihood
and Impact
Likelihood: Comparisons
The number of survey responses received from different regions
ranges from 64 from Sub-Saharan Africa to 330 from Europe.
For stakeholder groups the range was from 88 from international
organizations to 471 from business. As illustrated in Table 1, out
of 50 global risks, only two risks – extreme volatility in energy
and agriculture prices and major systemic financial failure – did
not have any statistically significant differences between any
groups. The other 48 risks had at least one group difference.
Arguably the risk with the most differences, especially between
regions, was failure of drug policies.
Only 8 out of 50 risks had statistically significant differences
between respondents under 40 and over 40 years of age. Four
of these risks were in the environmental category: failure of
climate change adaptation, irremediable pollution, rising
greenhouse gas emissions, and unprecedented geophysical
destruction.
Similarly, the environmental category had the largest percentage
of risks with statistically significant differences between experts
and non-experts. Where there are differences, generally experts
perceived the risk as more likely to occur, though non-experts
found four risks more likely: severe income disparity,
unmanageable inflation and deflation, rising religious fanaticism
and unforeseen consequences of nanotechnology. Interestingly,
rising religious fanaticism was one of the most highly connected
risks in the Risks Interconnection Map.
Finally, where there were statistically significant gender
differences, females were more pessimistic and rated the risks
as more likely to occur. The biggest difference between male
and female opinions was regarding the risk of unprecedented
geophysical destruction, with a difference of 0.41 (on a scale of 1
to 5).
Table 1-2: Legends
lv
lvi
62
The margin of error varies slightly across the 50 risks. See Table 3 in Appendix 2.
The margin of error varies across the five categories and the different possible answers.
Global Risks 2013
Region of Residence
Stakeholder
As
Asia
Ac
E
Europe
B
Business
LatAm
Latin America
G
Government
Academia
NthA
North America
IO
MENA
Middle East/ North Africa
N
NGO
SSA
Sub-Saharan Africa
Other
Other
Section 1
Table 1: Comparisons between Groupslvii for Likelihood of Global Risks Occurring in the Next 10 Yearslviii
Risk
Region of Residence
Stakeholder
Age
Gender
Under 40
Over 40
Expertise
Male
Female
Expert
Non-Expert
NthA > All other regions
-
-
-
4.02 > 3.91
NthA, SSA > E, LatAm
-
-
3.65 < 3.79
-
-
-
-
-
-
-
-
-
-
-
-
-
-
3.24 < 3.38
-
-
-
Extreme volatility in energy and
agriculture prices
NthA > E, LatAm, MENA, SSA
As > MENA
-
NthA, E, MENA > LatAm
-
-
-
NthA > As, E, LatAm
NGO > G
-
4.19 < 4.31
4.15 < 4.29
Unforeseen negative consequences of
regulation
NthA > LatAm
B > NGO, Ac, G, IO
-
-
3.41 > 3.21
Unmanageable inflation or deflation
As > NthA, E, LatAm
SSA > LatAm
-
3.25 > 3.11
-
3.12 < 3.24
NthA > As, LatAm
E > LatAm
Other > IO
-
-
3.67 > 3.36
NthA > As, E, MENA
NGO > G
3.69 < 3.81
3.71 < 3.89
4.04 > 3.69
3.48 > 3.24
3.25 < 3.6
3.62 > 3.28
-
3.54 < 3.77
3.91 > 3.53
-
3.64 < 3.8
3.9 > 3.64
-
3.64 < 3.85
4.07 > 3.61
-
4.28 > 3.86
-
mismanagement
NthA > As, E, MENA
NthA > As, E, MENA
NthA > As, E, MENA
NGO > IO
NGO > B
NthA > MENA
As > MENA, E
NthA > E
As > E, MENA
NthA > As, LatAm
Diffusion of weapons of mass destruction NthA > All other regions
-
3.14 < 3.3
NthA, LatAm > As, E
-
-
NthA > As, E, LatAm, SSA
NthA > As, LatAm
NGO > G
3.87 < 4
-
-
3.24 > 3.11
3.06 < 3.47
-
-
2.53 < 2.75
-
-
-
-
-
-
3.34 > 3.18
-
All other
stakeholders > G
-
3.4 < 3.61
4 > 3.6
-
3.57 > 3.41
-
-
E > As
-
-
-
-
As > LatAm
-
-
2.75 < 2.95
-
NthA > As, E
-
-
3.69 < 3.87
-
Terrorism
NthA > As, LatAm, E
-
-
-
-
NthA > MENA, LatAm, SSA
-
-
-
-
NthA > As, E, LatAm
-
-
3.38 < 3.57
-
NthA > LatAm
-
-
3.18 > 3.04
-
NthA > As, LatAm
-
-
3.55 < 3.71
3.69 > 3.52
LatAm, NthA > As, E, SSA
E > As
-
-
-
-
NthA, E > As, LatAm, SSA, MENA NGO > G
NthA > As, E, MENA, LatAm
NthA > As, E, LatAm
Unmanaged migration
NthA, E > As
-
-
-
3.37 < 3.57
3.52 > 3.36
-
-
-
3.59 < 3.71
-
3.34 < 3.63
-
3.5 > 3.36
-
3.52 > 3.38
3.39 < 3.6
3.53 > 3.37
NthA > E, MENA, LatAm
As > E
-
-
-
-
-
3.78 < 4.01
-
NthA, E, As, SSA > LatAm
Ac, Other > IO,
NGO
-
-
-
Cyber attacks
E > SSA
Ac, B, NGO > IO
-
-
4.01 > 3.75
As, E, NthA > MENA
B>G
3.13 > 2.96
As > LatAm
NthA > As, E, LatAm
Mineral resource supply vulnerability
Water supply crises
-
-
-
-
-
-
-
B > IO
-
-
3.68 > 3.46
E > LatAm, MENA
As > MENA
NGO, B > IO
-
-
-
-
Ac > IO
-
-
2.97 > 2.83
Unforeseen consequences of climate
change mitigation
NthA > E
Other > IO
-
3.17 < 3.36
-
-
nanotechnology
-
-
-
2.71 < 3
Unforeseen consequences of new life
science technologies
-
-
-
3.08 < 3.22
lvii
lviii
Section 6
-
Section 5
NGO > G
Section 4
Section 3
Section 2
2.69 < 2.83
-
An analysis of variance (ANOVA) tested whether or not the means of sub-groups were all equal. For those risks where they were not all equal, a Sidak post-hoc test established which of the
pair-wise differences between groups were significant at the 5% level.
Only statistically significant differences are noted; otherwise, the table cell is empty.
Global Risks 2013
63
Section 1
Impact: Comparisons
Section 2
In terms of perceived impact, regional differences were found for
48% of the risks, with the most differences found in the
environmental category and the least in the economic category
(see Table 2). Where there were statistically significant
differences, respondents from Latin America perceived 50% of
these risks as having higher impact than did respondents from
other regions. Apart from the risk mineral resource supply
vulnerability, European respondents generally perceived risks as
having lower impact.
Section 3
Among stakeholder groups, statistically significant differences
were found for less than half the risks, with NGOs perceiving
impacts to be higher and businesses lower. There were two
exceptions: hard landing of an emerging economy and
mismanagement of population ageing.
Between respondents under and over 40 years of age, there
were statistically significant differences for half the risks, with
younger respondents perceiving higher impact. The largest
difference, 0.32 units, was for irremediable pollution.
Section 4
Male and female opinions differed significantly for 39 out of 50
risks, most obviously in the geopolitical category, with all 10 risks
having differences. In all 39 cases, men perceived the impact of
the risks as lower, with the largest difference, of 0.43, for
entrenched organized crime.
Fewest statistically significant differences were found between
experts and non-experts – only 15 risks, none in the geopolitical
category and only one in the technological category. Where
there were differences, experts generally rated risks as having a
higher impact, except in the case of two risks: severe income
disparity and unforeseen consequences of nanotechnology.
Section 5
Section 6
64
Global Risks 2013
Section 1
Table 2: Comparisons between Groupslix for Impact of Global Risks if they were to Materializelx
Risk
Region of Residence
Stakeholder
Age
Gender
Under 40
-
-
-
-
Extreme volatility in energy and
agriculture prices
-
-
-
-
B, Ac > G
-
NthA > E
-
-
SSA > As, E
Ac, NGO, Other > B
Unforeseen negative consequences of
regulation
SSA > E, NthA
As > E
Other > Ac, IO
-
-
4.03 > 3.92
-
-
-
-
4.1 > 4
-
-
3.71 > 3.61
3.24 > 3.13
3.15 < 3.29
-
3.71 < 4.06
3.72 < 3.89
3.12 < 3.33
3.25 > 3.11
-
3.63 > 3.52
-
3.63 > 3.51
-
-
-
3.62 < 3.75
-
3.8 < 4.16
4.17 > 3.84
LatAm > E, NthA
mismanagement
LatAm > As, E
NGO > Ac, B
LatAm > E
NGO, Other > B
-
3.31 < 3.59
3.6 > 3.33
NthA, LatAm > E
NGO > B
-
3.56 < 3.87
3.95 > 3.57
NthA > As
NGO > B, G
-
3.82 < 4.04
4.23 > 3.8
NGO > B
-
3.29 < 3.55
3.72 > 3.27
3.25 < 3.55
-
-
NonExpert
3.84 < 3.98
NGO > B
Expert
3.68 < 3.88
-
Expertise
Female
-
NthA, LatAm, As > E
-
LatAm > NthA, E, As
-
-
-
Diffusion of weapons of mass destruction NthA > As
-
LatAm > As, E, NthA
IO, NGO > B
-
-
-
Other > B
-
-
LatAm > As, E
SSA > E
Terrorism
NthA, As, MENA > E
NGO > Ac, B, G
Other > B
-
NthA > E, As
Unmanaged migration
3.86 < 4.07
3.09 < 3.52
-
-
3.64 < 3.81
-
-
3.74 < 3.92
-
3.1 < 3.33
-
3.38 < 3.69
-
3.24 > 3.1
3.57 > 3.38
-
-
2.91 < 3.33
-
NGO > B
3.67 > 3.52
3.94 > 3.73
-
NGO, B > G
-
-
-
3.3 > 3.13
NGO > Ac, B
-
-
-
-
-
LatAm, NthA > E
-
3.5 < 3.63
3.5 < 3.82
-
3.61 > 3.46
-
3.36 < 3.53
-
-
-
LatAm > All other regions
3.72 > 3.54
NGO > IO
-
3.47 < 3.83
NGO > B
3.42 > 3.28
-
-
3.76 < 4.01
-
2.95 < 3.25
3.14 > 2.94
3.25 < 3.58
3.44 > 3.27
-
3.59 < 3.76
-
-
3.27 < 3.69
3.49 > 3.3
3.78 > 3.64
3.63 < 3.91
NthA > E
-
3.68 > 3.54
3.56 < 3.71
-
Water supply crises
LatAm > E, As
-
4.12 > 3.87
3.89 < 4.22
4.05 > 3.93
3.74 > 3.52
-
-
-
Cyber attacks
-
-
-
-
3.05 > 2.94
-
3.47 < 3.63
-
3.8 > 3.63
-
MENA > E, NthA
-
3.36 > 3.15
3.15 < 3.48
-
MENA, LatAm > E
-
3.34 > 3.21
3.2 < 3.46
-
E > NthA
NGO > IO
-
-
-
LatAm, As > NthA
NGO > B, IO
Other > IO
-
2.73 < 2.96
-
-
3.27 < 3.57
-
Unforeseen consequences of climate
change mitigation
-
Other > B
nanotechnology
-
NGO > B, IO
3.09 > 2.91
2.9 < 3.23
2.84 < 3.04
Unforeseen consequences of new life
science technologies
-
NGO > IO
3.43 > 3.3
3.29 < 3.53
-
lix
lx
Section 6
-
Section 5
MENA > As, E, NthA
LatAm > As, E
SSA > E
-
3.55 < 3.92
Section 4
3.82 > 3.5
3.66 > 3.5
3.45 > 3.24
Section 3
3.86 > 3.62
Male
Section 2
Over 40
An analysis of variance (ANOVA) tested whether or not the means of sub-groups were all equal. For those risks where they were not all equal, a Sidak post-hoc test established which of the
pair-wise differences between groups were significant at the 5% level.
Only statistically significant differences are noted; otherwise, the table cell is left empty.
Global Risks 2013
65
Section 1
Likelihood and Impact – Average Scores
and Margin of Error
Section 2
The table below shows the average likelihood and impact scores
and their margins of error (based on a 95% confidence level).
The larger the margin of error, the lower the confidence that the
result is close to the “true” figure of the whole survey populations
(see Appendix 1).
Appendix 3
Resilience
Table 3: Average Likelihood and Impact Scores and their
Margin of Error
Section 3
Section 4
Section 5
Section 6
Risk
Likelihood
Impact
3.97 +/- 0.05
3.97 +/- 0.05
3.69 +/- 0.05
3.73 +/- 0.05
3.71 +/- 0.05
3.88 +/- 0.05
3.46 +/- 0.05
3.49 +/- 0.05
3.44 +/- 0.06
4.04 +/- 0.05
3.32 +/- 0.06
3.19 +/- 0.05
3.36 +/- 0.05
3.66 +/- 0.05
4.22 +/- 0.05
3.8 +/- 0.05
3.31 +/- 0.06
3.18 +/- 0.06
3.18 +/- 0.05
3.57 +/- 0.05
3.42 +/- 0.06
3.57 +/- 0.06
3.76 +/- 0.06
3.9 +/- 0.06
3.35 +/- 0.06
3.65 +/- 0.06
3.61 +/- 0.06
3.57 +/- 0.05
3.69 +/- 0.06
3.39 +/- 0.06
3.7 +/- 0.06
3.65 +/- 0.06
3.94 +/- 0.05
3.88 +/- 0.05
3.68 +/- 0.06
3.36 +/- 0.06
3.17 +/- 0.06
3.33 +/- 0.06
2.59 +/- 0.06
3.16 +/- 0.06
3.38 +/- 0.06
3.53 +/- 0.05
3.23 +/- 0.06
3.92 +/- 0.06
3.46 +/- 0.06
3.21 +/- 0.06
3.58 +/- 0.06
3.69 +/- 0.05
3.69 +/- 0.06
3.79 +/- 0.05
2.81 +/- 0.06
3.16 +/- 0.06
3.74 +/- 0.06
3.47 +/- 0.06
Terrorism
3.64 +/- 0.06
3.59 +/- 0.06
3.35 +/- 0.06
3.4 +/- 0.06
3.43 +/- 0.06
3.03 +/- 0.06
3.14 +/- 0.06
3.34 +/- 0.06
3.6 +/- 0.06
3.83 +/- 0.06
3.41 +/- 0.06
3.03 +/- 0.06
3.83 +/- 0.05
3.67 +/- 0.05
3.43 +/- 0.06
3.35 +/- 0.05
3.66 +/- 0.06
3.64 +/- 0.06
Unmanaged migration
3.42 +/- 0.06
3.39 +/- 0.06
3.45 +/- 0.06
3.71 +/- 0.06
3.2 +/- 0.06
3.6 +/- 0.06
Water supply crises
3.85 +/- 0.05
3.98 +/- 0.05
2.96 +/- 0.06
3.62 +/- 0.06
Cyber attacks
3.82 +/- 0.06
3.52 +/- 0.06
3 +/- 0.06
2.99 +/- 0.06
3.36 +/- 0.07
3.24 +/- 0.06
3.52 +/- 0.06
3.27 +/- 0.06
3.42 +/- 0.06
3.45 +/- 0.06
2.87 +/- 0.06
2.8 +/- 0.06
Unforeseen consequences of climate change
mitigation
3.23 +/- 0.06
3.35 +/- 0.06
2.79 +/- 0.06
2.99 +/- 0.06
Unforeseen consequences of new life science
technologies
3.11 +/- 0.06
3.36 +/- 0.06
66
Global Risks 2013
Appendix 3.1
Over 14,000 respondents to the World Economic Forum’s
Executive Opinion Surveylxi were asked to rate their
government’s risk management effectiveness:
How would you assess your national government’s overall
risk management effectiveness of monitoring, preparing for,
responding to and mitigating against major global risks (e.g.
financial crisis, natural disasters, climate change,
pandemics, etc.)? (1 = Not effective in managing major
global risks; 7 = Effective in managing major global risks)
Table 4 provides the average results for each country, ranked
from highest (best) to lowest (worst). Singapore and many
innovation-driven economies (Stage 3 in the Forum’s Global
Competitiveness Index) are ranked higher than factor-driven
(Stage 1) economies (for definitions of stages, see page 68). The
table also gives the survey sample size and the margin of error
for each country, its ISO code, and development stage.
Countries marked in light blue were used for the preliminary
analysis presented in the Special Report section; the selection
criterion was the available sample size from the Global Risks
Perception Survey (see Table 5).
lxi
The Executive Opinion Survey is the Forum’s flagship opinion poll that is conducted every
year to sample the perception of top managers from small- and medium-sized firms on the
economies in which they are operating.
Section 1
Economic
Development
Stage
Sample
Risk Management
Score
Margin of Error at
95% Confidence
Level
0.11
55
Tajikistan
TJK
Stage 1
97
3.91
0.35
6.01
0.18
56
Macedonia, FYR
MKD
Stage 2
86
3.90
0.35
3
Oman
OMN
Transition from 2 to 3
75
5.55
0.26
57
Poland
POL
205
3.87
0.19
4
United Arab
Emirates
ARE
Stage 3
163
5.47
0.17
58
Czech Republic
CZE
Stage 3
159
3.87
0.25
59
Peru
PER
Stage 2
83
3.83
0.31
5
Canada
CAN
Stage 3
101
5.41
0.20
60
Ethiopia
ETH
Stage 1
57
3.83
0.34
6
Sweden
SWE
Stage 3
76
5.41
0.28
61
Uruguay
URY
80
3.80
0.33
7
Saudi Arabia
SAU
94
5.41
0.29
62
Austria
AUT
Stage 3
105
3.80
0.29
8
New Zealand
NZL
Stage 3
52
5.40
0.24
63
Cape Verde
CPV
Stage 2
103
3.75
0.27
9
Finland
FIN
Stage 3
36
5.32
0.43
64
Lithuania
LTU
148
3.74
0.25
0.34
ISO
Rank
6.08
113
Country
Margin of Error at
95% Confidence
Level
Risk Management
Score
171
Sample
Stage 3
QAT
Economic
Development
Stage
SGP
Qatar
ISO
Country
Singapore
2
Chile
CHL
78
5.20
0.29
65
Ireland
IRL
Stage 3
60
3.70
11
Norway
NOR
Stage 3
74
5.15
0.24
66
Philippines
PHL
126
3.69
0.25
12
Mexico
MEX
268
5.13
0.15
67
Japan
JPN
Stage 3
111
3.67
0.28
13
Netherlands
NLD
Stage 3
81
5.06
0.25
68
Armenia
ARM
Stage 2
77
3.65
0.28
14
Malaysia
MYS
78
4.97
0.25
69
Burkina Faso
BFA
Stage 1
39
3.64
0.46
15
Hong Kong SAR
HKG
Stage 3
68
4.96
0.35
70
Benin
BEN
Stage 1
81
3.62
0.40
16
Kazakhstan
KAZ
100
4.93
0.35
71
Guinea
GIN
Stage 1
57
3.61
0.44
17
Germany
DEU
Stage 3
127
4.90
0.25
72
Namibia
NAM
Stage 2
81
3.60
0.32
18
Turkey
TUR
84
4.83
0.28
73
RUS
413
3.60
0.14
19
Switzerland
CHE
Stage 3
77
4.82
0.32
Russian
Federation
United Kingdom
GBR
Stage 3
102
4.81
0.28
74
Iceland
ISL
Stage 3
92
3.58
0.31
21
Botswana
BWA
78
4.80
0.27
75
Iran, Islamic Rep.
IRN
560
3.57
0.13
22
Gambia, The
GMB
Stage 1
84
4.78
0.26
76
Nicaragua
NIC
Stage 1
77
3.57
0.25
23
Taiwan, China
TWN
Stage 3
70
4.75
0.26
77
Zambia
ZMB
Stage 1
88
3.57
0.33
24
Brunei
Darussalam
BRN
41
4.75
0.39
78
Mozambique
MOZ
Stage 1
87
3.56
0.35
79
Liberia
LBR
Stage 1
84
3.56
0.31
25
Luxembourg
LUX
Stage 3
44
4.65
0.43
80
Jamaica
JAM
Stage 2
75
3.53
0.30
26
Azerbaijan
AZE
89
4.63
0.30
81
Ghana
GHA
Stage 1
77
3.53
0.31
27
Mauritius
MUS
Stage 2
91
4.58
0.31
82
Bolivia
BOL
71
3.52
0.27
28
Estonia
EST
82
4.54
0.31
83
Côte d'Ivoire
CIV
Stage 1
91
3.46
0.30
29
United States
USA
Stage 3
390
4.53
0.14
84
Costa Rica
CRI
Stage 2
94
3.44
0.27
30
China
CHN
Stage 2
369
4.51
0.13
85
Colombia
COL
Stage 2
281
3.43
0.17
31
France
FRA
Stage 3
128
4.51
0.27
86
Vietnam
VNM
Stage 1
94
3.40
0.30
32
Australia
AUS
Stage 3
67
4.49
0.41
87
Timor-Leste
TLS
Stage 2
33
3.39
0.61
88
Dominican
Republic
DOM
Stage 2
90
3.38
0.32
0.33
Bahrain
BHR
63
4.47
0.38
34
South Africa
ZAF
Stage 2
45
4.42
0.38
35
Malta
MLT
Stage 3
57
4.36
0.44
89
Senegal
SEN
Stage 1
91
3.35
36
Gabon
GAB
48
4.34
0.36
90
Libya
LBY
68
3.33
0.40
37
Morocco
MAR
Stage 2
40
4.33
0.45
91
Mongolia
MNG
82
3.27
0.31
38
India
IND
Stage 1
119
4.31
0.27
92
Bulgaria
BGR
Stage 2
119
3.26
0.24
39
Italy
ITA
Stage 3
86
4.24
0.32
93
Latvia
LVA
98
3.24
0.29
40
Barbados
BRB
69
4.24
0.34
94
Stage 2
100
3.22
0.24
Korea, Rep.
KOR
Stage 3
98
4.23
0.25
Bosnia and
Herzegovina
BIH
41
42
Montenegro
MNE
Stage 2
74
4.20
0.35
95
Cameroon
CMR
Stage 1
61
3.21
0.36
43
Seychelles
SYC
32
4.20
0.51
96
TTO
149
3.21
0.23
44
Israel
ISR
Stage 3
50
4.19
0.40
Trinidad and
Tobago
45
Brazil
BRA
141
4.16
0.23
46
Panama
PAN
Stage 2
132
4.15
0.20
47
Denmark
DNK
Stage 3
128
4.10
0.28
48
Cambodia
KHM
Stage 1
73
4.09
0.33
49
Indonesia
IDN
Stage 2
88
4.08
0.32
50
Belgium
BEL
Stage 3
83
4.07
0.36
51
Portugal
PRT
Stage 3
114
4.06
0.25
52
Puerto Rico
PRI
Stage 3
70
4.05
0.40
53
Spain
ESP
Stage 3
90
4.03
0.36
54
Jordan
JOR
Stage 2
155
3.92
0.24
lxii
Countries highlighted had sufficient sample sizes based on responses for the Global Risks
Perception Survey.
97
Suriname
SUR
Stage 2
36
3.17
0.37
98
Slovak Republic
SVK
Stage 3
65
3.11
0.33
99
Mali
MLI
Stage 1
99
3.06
0.35
100
Malawi
MWI
Stage 1
60
3.05
0.38
101
Nigeria
NGA
Stage 1
102
3.05
0.31
102
Guatemala
GTM
Stage 2
83
3.04
0.29
103
Hungary
HUN
103
3.03
0.32
104
Bangladesh
BGD
Stage 1
84
3.03
0.31
105
Egypt
EGY
73
3.02
0.33
106
Guyana
GUY
Stage 2
89
3.02
0.31
107
Croatia
HRV
107
3.00
0.23
Section 6
33
Section 5
20
Section 4
10
Section 3
1
Table continued on next page
Global Risks 2013
Section 2
Rank
Table 4: Executive Opinion Survey Question 2.07 Risk
Management Effectiveness Resultslxii
67
Margin of Error at
95% Confidence
Level
Economic
Development
Stage
Uganda
UGA
Stage 1
87
2.99
0.30
109
Thailand
THA
Stage 2
75
2.98
0.37
110
Cyprus
CYP
Stage 3
78
2.97
0.30
111
Mauritania
MRT
Stage 1
78
2.97
0.37
112
Kenya
KEN
Stage 1
109
2.93
0.31
113
Moldova
MDA
Stage 1
112
2.93
0.25
114
Tanzania
TZA
Stage 1
97
2.90
0.29
115
Lesotho
LSO
Stage 1
80
2.87
0.34
116
Slovenia
SVN
Stage 3
109
2.84
0.28
117
Kuwait
KWT
37
2.81
0.62
118
Serbia
SRB
Stage 2
99
2.81
0.31
119
Ukraine
UKR
Stage 2
108
2.65
0.27
120
Nepal
NPL
Stage 1
91
2.64
0.28
Sample
ISO
Section 3
Country
Section 2
Rank
Risk Management
Score
Section 1
108
Section 4
121
Algeria
DZA
33
2.64
0.57
122
Sierra Leone
SLE
Stage 1
99
2.59
0.31
123
Romania
ROU
Stage 2
98
2.53
0.27
124
Swaziland
SWZ
Stage 2
50
2.52
0.39
125
Chad
TCD
Stage 1
103
2.49
0.27
126
Pakistan
PAK
Stage 1
106
2.47
0.24
127
Zimbabwe
ZWE
Stage 1
63
2.46
0.28
0.27
Section 5
128
Honduras
HND
85
2.43
129
Lebanon
LBN
38
2.42
0.39
130
Madagascar
MDG
Stage 1
88
2.40
0.21
131
Paraguay
PRY
Stage 2
78
2.29
0.26
132
El Salvador
SLV
Stage 2
34
2.28
0.41
133
Kyrgyz Republic
KGZ
Stage 1
96
2.21
0.26
134
Burundi
BDI
Stage 1
90
2.18
0.21
135
Haiti
HTI
Stage 1
66
2.16
0.29
136
Greece
GRC
Stage 3
78
2.12
0.23
137
Yemen
YEM
Stage 1
52
2.12
0.35
138
Argentina
ARG
96
2.08
0.25
139
Venezuela
VEN
38
1.68
0.28
Meanwhile, respondents to the Global Risks Perception Survey
were asked, per risk, about their country of expertise’s ability to
adapt and or recover from its impact:
“What would be your country’s capability to adapt and or
recover from the national impact of this global risk?”
Table 5 ranks the countries from the highest to lowest according
to their adaptability/ recoverability score. As with the Executive
Opinion Survey risk-management question results, Singapore
again and many Stage 3, innovation-driven economies are
ranked higher than Stage 1, factor-driven economies. Additional
details about the survey sample size for each country and its
economic development stage are also provided in the table.
Analysing the countries in table 5 in terms of their economic
development stage presents an interesting way to group
countries and tests whether this is the best method to do so.lxiii In
the Global Competitiveness Report 2012-2013, the economic
development stages are as defined below:
- Economies in the first stage are mainly factor-driven and
compete based on their factor endowments—primarily
low-skilled labour and natural resources.
- Transition from stage 1 to stage 2
- Economies in the second stage have moved into an
efficiency-driven stage of development, when they must
begin to develop more efficient production processes and
increase product quality because wages have risen and they
cannot increase prices.
- Transition from stage 2 to stage 3
- Economies in stage 3 have moved into the innovation-driven
stage, wages will have risen by so much that they are able to
sustain those higher wages and the associated standard of
living only if their businesses are able to compete with new
and/or unique products, services, models, and processes.
Countries highlighted in blue were used for the preliminary
analysis presented in the Special Report section. The selection
criterion was the sufficiency of the country sample size to
guarantee a margin of error smaller than 0.5 units (equal to a
95% confidence interval of less than one unit). 66 countries were
not included below as the sample size was smaller than 5.lxiv
Section 6
lxiii
lxiv
68
Global Risks 2013
The economic development stage groupings are the best data currently available for this
report. Further analysis will investigate other potential groups, for example, GDP per capita
or income level.
Margin of errors can still be large for the countries with small sample sizes listed in Table 5
and therefore were not included in the detailed analysis.
Section 1
3.46
1.07
32
3.37
0.43
5
United Arab
Emirates
Stage 3
11
3.28
1.01
6
Canada
Stage 3
18
3.27
0.63
7
People's Republic
of China
Stage 2
72
3.26
0.25
8
Chile
6
3.24
1.71
9
USA
Stage 3
283
3.23
0.12
10
Denmark
Stage 3
8
3.21
1.20
11
Netherlands
Stage 3
20
3.19
0.51
12
Germany
Stage 3
40
3.19
0.36
13
Israel
Stage 3
8
3.16
1.26
14
Australia
Stage 3
13
3.15
0.76
15
Belgium
Stage 3
7
3.15
1.35
16
Japan
Stage 3
60
3.07
0.29
17
Brazil
35
3.01
0.44
18
South Korea
Stage 3
6
2.96
1.32
19
United Kingdom
Stage 3
64
2.95
0.29
20
Mexico
25
2.93
0.52
21
Indonesia
Stage 2
9
2.9
1.08
22
Saudi Arabia
9
2.87
1.21
23
Poland
14
2.86
0.74
24
Tunisia
Stage 2
16
2.85
0.77
25
Russian Federation
35
2.84
0.48
26
France
Stage 3
6
2.81
1.63
27
Vietnam
Stage 1
13
2.79
0.77
28
South Africa
Stage 2
25
2.77
0.57
29
Thailand
Stage 2
6
2.75
1.51
30
Costa Rica
Stage 2
11
2.74
0.97
31
Peru
Stage 2
6
2.73
1.65
32
India
Stage 1
64
2.71
0.28
33
Panama
Stage 2
13
2.67
0.95
34
Italy
Stage 3
31
2.67
0.40
35
Malaysia
10
2.64
0.80
Turkey
11
2.61
0.95
37
Ukraine
Stage 2
11
2.54
0.99
38
Kuwait
7
2.52
1.48
39
Egypt
10
2.47
0.89
40
Mauritius
Stage 2
9
2.46
1.01
41
Argentina
6
2.46
1.41
42
Dominican
Republic
Stage 2
5
2.44
1.94
43
Spain
Stage 3
9
2.4
1.10
44
Philippines
9
2.4
0.89
45
Pakistan
Stage 1
10
2.37
1.17
46
Colombia
Stage 2
7
2.34
1.20
47
Jordan
Stage 2
7
2.23
1.48
48
Nigeria
Stage 1
16
2.21
0.66
49
Ethiopia
Stage 1
7
2.08
1.41
Monitoring
system
health
Logistics Performance Index from the
Quality of natural
World Bank
environment
Quality of
healthcare system
Quality of overall
infrastructure
Quality of
education system
Modularity
State cluster
development
Economic Freedom of the World Index
from Gwartney, J., Lawson, R., & Clark,
J. R. Economic Freedom of the world,
2012.
Adaptive
decisionmaking
models
Willingness to
delegate authority
Index of Economic Freedom from 2012
Index of Economic Freedom, the
Heritage Foundation.
Redundancy Quantity of local
of critical
suppliers
infrastructure
Reserves
Renewable freshwater resources
Density of physicians from World Health
Statistics, World Health Organization.
Diversity of
solutions
and strategy
Value chain
breadth
Environmental Performance Index
(Ecosystem Vitality) from Environmental
Performance Index, Yale University.
Capacity for
selforganization
Education Index from International
Accessibility of
Human Development Indicators, United
digital content
Nations Development Programme.
Extent to which
virtual social
networks are used
Creativity
and
innovation
Latest
technologies
Research and development expenditure
as a percentage of gross domestic
production from World Development
Indicators, the World Bank.
Communication
Public trust in
politicians
Media Sustainability Index from IREX.
Inclusive
participation
Businessgovernment
relations
Business regulatory environment
Structural policies cluster from Country
Policy and Institutional Assessment, the
World Bank.
Responsive Reform
regulatory
implementation
feedback
efficiency
mechanisms
Actionable Governance Indicators from
Actionable Governance Indicators Data
Portal, the World Bank.
Active
“horizon
scanning”
Some studies have suggested potential
quantitative data for this attribute including
developing public-private partnerships for
Research and Development and
Innovation and promoting centres and
networks of excellence, regional research
driven clusters and innovation poles
(Manjón, J. & Vicente J. A Proposal of
Indicators and Policy Framework for
Innovation Benchmark in Europe. In
Journal of Technology Management and
Innovation, 2010, 5:13-23.)
Collaboration
within clusters
Section 6
36
Potential
Quantitative
Indicators
8
Stage 3
Potential
Executive
Opinion
Survey
Indicators
Stage 3
Switzerland
Component
Attributes
Margin of Error at
95% Confidence
Level
Sweden
4
Robustness Resilience
Components
Adaptability/
Recoverability
Score
3
Table 6: Potential Indicators for Resilience Componentslxvi
Redundancy
Sample
1.62
Resourcefulness
Economic
Development
Stage
0.93
3.56
Response
Country
3.66
6
Recovery
Rank
10
Stage 3
Table 7 shows the questions identified in the Executive Opinion
Survey that are potential variables for the Country Resilience
framework described in the Special Report section of this report.
lxv
lxvi
See Table 7 for detailed questions for each of the qualitative indicators.
These potential indicators are still work in progress. Further development, research and
refinement will be conducted in the coming year.
Global Risks 2013
Section 5
Stage 3
Norway
Section 4
Singapore
2
As presented in the Special Report section, a country system is
assessed using five components of resilience: robustness,
redundancy, resourcefulness, response and recovery. Each
component is further defined by key attributes, and for each of
these attributes, potential qualitativelxv and quantitative indicators
have been identified (see Table 6).
Section 3
1
Appendix 3.2
Section 2
*by country of expertise
Table 5: Global Risks Perception Survey Resilience Question
Results
69
Section 1
Table 7: Executive Opinion Survey Questions
Section 2
Section 3
Section 4
Question Variable Name
Executive Opinion Survey Question
0208
Businessgovernment
relations
How would you characterize business-government
relations in your country? (1 = Generally
confrontational; 7 = Generally cooperative )
0304
Public trust of
politicians
How would you rate the level of public trust in the
ethical standards of politicians in your country? (1 =
Very low; 7 = Very high)
0305
Reform
implementation
efficiency
In your country, to what extent are government
reforms implemented efficiently? (1 = Reforms are
never implemented; 7 = Reforms are implemented
highly efficiently)
0306
Politicians' ability
to govern
In your country, how you would rate the ability of
politicians to govern effectively? (1 = Very weak; 7 =
Very strong)
0308
Wastefulness of
government
spending
How would you rate the composition of public spending
in your country? (1 = Extremely wasteful; 7 = Highly
efficient in providing necessary goods and services )
0510
Government
provision of services
for improved business
performance
To what extent does the government in your country
continuously improve its provision of services to help
businesses in your country boost their economic
performance? (1 = Not at all; 7 = Extensively)
0401
Quality of overall
infrastructure
How would you assess general infrastructure (e.g.
transport, telephony and energy) in your country? (1
= Extremely underdeveloped; 7 = Extensive and
efficient by international standards)
0501
Availability of latest To what extent are the latest technologies available in
technologies
your country? (1 = Not available; 7 = Widely available)
0507
Collaborations
within clusters
In your country, how extensive is collaboration among firms
(e.g. suppliers, competitors, clients) in order to promote
knowledge flows and innovation? (1 = Collaboration is
non-existent; 7 = Collaboration is extensive)
0524
Accessibility of
digital content
In your country, how accessible is digital content (e.g.
text and audio-visual content, software products) via
multiple platforms (e.g. fixed-line Internet, wireless
Internet, mobile network, satellite)? (1 = Not accessible
at all; 7 = Widely accessible)
Section 5
Section 6
0525
Extent of virtual
social networks
use
How widely used are virtual social networks (e.g.
Facebook, Twitter, LinkedIn) for professional and
personal communications in your country? (1 = Not
used at all; 7 = Used widely)
0803
Local supplier
quantity
How numerous are local suppliers in your country? (1
= Largely non-existent; 7 = Very numerous)
0809
State of cluster
development
In your country, how prevalent are well-developed and
deep clusters (geographic concentrations of firms,
suppliers, producers of related products and services,
and specialized institutions in a particular field)? (1 =
Non-existent; 7 = Widespread in many fields)
0902
Value chain
breadth
In your country, do exporting companies have a narrow
or broad presence in the value chain? (1 = Narrow,
primarily involved in individual steps of the value chain
(e.g., resource extraction or production); 7 = Broad,
present across the entire value chain (i.e. do not only
produce but also perform product design, marketing
sales, logistics and after-sales services))
0910
Willingness to
delegate authority
In your country, how do you assess the willingness to
delegate authority to subordinates? (1 = Not willing
– top management controls all important decisions; 7
= Very willing – authority is mostly delegated to
business unit heads and other lower-level managers)
1001
Quality of the
educational
system
How well does the educational system in your
country meet the needs of a competitive economy?
(1 = Not well at all; 7 = Very well)
1102
Measures to
In your country, how effective are the government’s
combat corruption efforts to combat corruption and bribery? (1 = Not
and bribery
effective at all; 7 = Extremely effective)
1303
Quality of natural
environment
How would you assess the quality of the natural
environment in your country? (1 = Extremely poor; 7
= Among the world’s most pristine)
1401
Quality of
healthcare
services
How would you assess the quality of healthcare
(public and private) provided for ordinary citizens in
your country? (1 = Very poor; 7 = Excellent, among
the best healthcare delivery systems of the world)
Appendix 3.3
As explained in the Special Report, 10 countries were identified
that had a margin of error of less than 0.5: Brazil, China,
Germany, India, Italy, Japan, Russia, Switzerland, United
Kingdom and United States. Statistical analysislxvii was
conducted to identify paired differences between groups for the
10 countries, regionslxviii and economic development stages.lxix
Generally, respondents from Stage 3, innovation-driven
economies had greater confidence that their country will be able
to adapt and/or recover from the impact of a global risk.
Respondents from Stage 1, factor-driven economies, were more
pessimistic. Most interestingly, in the societal category, we found
the only risk that had no statistically significant difference,
mismanagement of population ageing, and the only risk where
Stage 2, efficiency-driven economies were more optimistic than
Stage 3 economies was rising religious fanaticism.
Following similar patterns, North Americans generally had
greater confidence, while Sub-Saharan Africans had less.
Statistically significant differences between countries were found
for all risks, other than the two risks hard landing of an emerging
economy and species overexploitation. Depending on the
category and sometimes the risk, different countries were seen
to have comparatively higher ability to adapt and/or recover from
the impact of the risks. For the economic and environmental
categories, it was Switzerland; for the geopolitical, it was China;
for the technological, it was the United States; and for the
societal category, there was no one particular country.
Across 50 global risks, where there are statistically significant
differences (56% of the risks for age and 44% of the risks for
gender), respondents under 40 years of age and female
respondents rate their country as having less ability to adapt
and/or recover from the impact of the risk. The majority of risks
that had no statistically significant differences were from the
geopolitical and technological category for gender and the
environmental category for age. The largest differences in
opinion were found on the unsustainable population growth and
water supply crises.
With regards to perceptions of experts versus non-experts,
unlike with likelihood and impact, for this group statistically
significant differences were found only in the societal and
technological category. Self-identified societal experts were
more pessimistic about our recovery from societal risks, while
self-identified technological experts were more optimistic about
our recovery from technological risks.
lxvii
lxviii
lxix
70
Global Risks 2013
An analysis of variance (ANOVA) tested whether or not the means of sub-groups were all
equal. For those risks where they were not all equal, a Sidak post-hoc test established
which of the pair-wise differences between groups were significant at the 5% level.
The whole survey sample was used.
The whole survey sample was used and grouped according to their economic
development stages as identified by the Global Competitiveness Report.
Section 1
Table 8: Comparisons between Groupslxx for a Country’s Ability to Adapt and/or Recover from the Impact of Global Riskslxxi
Country of Expertise
Brazil
Region of Eexpertise
BRA
Asia
Economic Development
Stages
A
Stakeholder
Stage 3
S3
Academia
A
CHN
Europe
E
T2.5
Business
B
Germany
DEU
Latin America
LA
Stage 2
S2
Government
G
India
IND
North America
NA
T1.5
IO
Italy
ITA
Middle East/ North Africa
MENA
Stage 1
S1
NGO
N
Japan
JPN
Sub-Saharan Africa
SSA
Other
Other
Russia
RUS
Switzerland
CHE
United Kingdom
GBR
United States
USA
Country of Expertise
*only for the 10 identified
countries
Region of
Expertise
Economic
Development
Stages
Stakeholder
Age
Gender
Under
40
CHE > GBR, IND,
ITA, JPN, USA
CHN > GBR, ITA,
JPN, USA
DEU, BRA > JPN
Chronic labour
market
imbalances
Extreme volatility
in energy and
agriculture prices
Female
Expert
NonExpert
-
T2.5 > S1, T1.5, S3
S2, S3 > S1
-
2.91
<
3.11
3.06
>
2.91
-
CHE > GBR, IND,
ITA, JPN, USA
CHN > IND, ITA, USA
DEU, BRA, USA >
ITA
LA, A, E, NA > SSA
T2.5, S3 > S1, T1.5
S2 > S1
-
2.86
<
3.09
3.04
>
2.86
-
CHN, USA > GBR,
IND, JPN
BRA > IND, JPN
CHE, DEU > JPN
NA > E, A, LA, SSA
MENA, E, A, LA >
SSA
S3 > S1, T1.5, S2
S2, T2.5 > S1
-
2.93
<
3.06
NA > E, SSA
S3 > All other
stages
S2 > S1
-
-
CHN > GBR, RUS
USA > GBR
NA, A > E
S2, T2.5, S3 > S1
Prolonged
infrastructure
neglect
CHE, CHN > BRA,
GBR, IND, ITA, RUS,
USA
DEU, JPN > BRA,
GBR, IND, ITA, RUS
USA > IND
A > LA, SSA
E, NA > SSA
S3 > S1, T1.5, T2.5
S2 > S1, T1.5
T2.5 > S1
Recurring liquidity CHN > GBR, ITA
crises
CHE, USA > ITA
A > E, SSA
NA > SSA
S2, T2.5, S3 > T1.5,
S1
Severe income
disparity
DEU > GBR, IND,
RUS, USA
CHE, JPN > IND
E > LA, SSA
MENA, NA, A >
SSA
Unforeseen
negative
consequences of
regulation
CHE, CHN > IND,
ITA, RUS
DEU, USA > ITA
Unmanageable
inflation or deflation
-
-
2.85
<
3.01
2.98
>
2.83
-
2.92
<
3.06
3.06
>
2.85
-
G > IO, N
2.92
<
3.17
3.11
>
2.91
-
S3 > All other
stages
S2, T2.5 > S1
B>N
2.7
<
2.89
2.87
>
2.64
-
NA > SSA
S3 > S1, T1.5, T2.5
S2 > S1, T1.5
A, B > IO
2.85
<
3.02
2.98
>
2.84
-
CHN, USA > IND
NA > SSA
S3 > S1, T1.5, S2
S2, T2.5 > S1, T1.5
G > IO
2.86
<
3.06
3.01
>
2.84
-
Antibioticresistant bacteria
CHE, JPN, USA >
BRA, IND, RUS
A, E, NA > LA, SSA
MENA > SSA
S3 > All
S2, T2.5 > S1
-
-
-
-
Failure of climate
change
adaptation
CHE, CHN, DEU,
JPN, USA > IND
A, E, NA > SSA
S3 > S1, T1.5
S2, T2.5 > S1
-
-
-
-
Irremediable
pollution
CHE > CHN, IND, ITA
GBR, JPN, USA >
IND, ITA
DEU > IND
NA > SSA, LA
A, E > SSA
S3 > All other
stages
T2.5 > S1, T1.5
S2 > S1
-
lxx
lxxi
B, G > IO
-
-
2.81
<
2.97
2.96
>
2.73
Section 6
Major systemic
financial failure
-
-
Section 5
Hard landing of
an emerging
economy
Male
Expertise
Section 4
Chronic fiscal
imbalances
Over
40
Section 3
Risk
Section 2
China
-
An analysis of variance (ANOVA) tested whether or not the means of sub-groups are all equal; for those that were not all equal, a Sidak post-hoc test was then conducted to establish which of the
pair-wise differences between groups are significant at the 5% level.
Only statistically significant differences are noted; otherwise, the table cell is left empty.
Global Risks 2013
71
Section 1
CHE > CHN, IND,
ITA, RUS
JPN > IND, ITA
BRA, DEU, GBR,
USA > IND
NA > SSA, LA
A, E > SSA
S3 > All other
stages
T2.5 > S1, T1.5
S2 > S1
-
Mismanaged
urbanization
CHE > BRA, CHN,
IND, RUS
DEU, JPN > BRA,
IND, RUS
CHN, GBR, USA >
BRA, IND
ITA > IND
E > A, MENA, SSA,
LA
A, NA > SSA, LA
S3 > All other
stages
S2 > S1, T1.5
T2.5 > S1
-
Persistent
extreme weather
CHE > BRA, IND, ITA
DEU, JPN > IND, ITA
CHN, GBR, USA >
IND
NA, E > SSA, LA
A > SSA
S3 > All other
stages
S2, T2.5 > S1
Rising
greenhouse gas
emissions
CHN, JPN > GBR,
IND, USA
BRA, CHE, DEU >
IND
-
-
Section 2
Land and
waterway use
mismanagement
Section 3
Species
overexploitation
-
2.85
<
3.01
3.02
>
2.74
-
-
3.12
>
2.93
-
-
-
2.98
>
2.80
-
S2, T2.5, S3 > S1,
T1.5
-
-
-
-
S3 > S1, T1.5
T2.5 > T1.5
-
-
-
-
-
-
-
-
-
-
Section 4
Section 5
Section 6
Unprecedented
geophysical
destruction
CHN, DEU > ITA
JPN, USA > IND, ITA
NA > MENA, LA, E,
SSA
A > MENA, SSA
E > SSA
S3 > S1, T1.5, S2
T2.5 > S1, T1.5
S2 > S1
Vulnerability to
geomagnetic
storms
CHN > BRA
USA > BRA, ITA
NA > E, LA, MENA,
SSA
A > MENA, LA,
SSA
E > LA
S3 > All other
stages
-
Critical fragile
states
CHE > ITA, JPN, RUS
CHN > ITA
A, E, NA > SSA
S3 > S1, T1.5, S2
T2.5 > S1, T1.5
S2 > S1
-
Diffusion of
weapons of mass
destruction
CHN, USA > ITA,
JPN
A, NA > LA, SSA
E > SSA
S3 > S1, T1.5
S2 > S1
-
Entrenched
organized crime
CHN, USA > BRA,
ITA, JPN, RUS
CHE, DEU, GBR >
ITA, RUS
IND, JPN > ITA
NA > E, LA, SSA,
A, E, MENA > LA,
SSA
S3 > All other
stages
-
2.95
<
3.13
Failure of
diplomatic
conflict resolution
CHE, CHN > ITA,
JPN, RUS
BRA, USA > ITA,
JPN
DEU, GBR > JPN
NA > LA, SSA
S3 > S1, T1.5, S2
T2.5 > S1
-
3.01
<
3.13
Global
governance
failure
CHN > IND, ITA, JPN,
RUS
CHE > ITA, JPN, RUS
USA > ITA
A, NA > SSA
S3 > S1, T1.5
S2 > S1
-
Militarization of
space
USA > BRA, DEU,
GBR, IND, ITA, JPN
CHN > GBR, ITA,
JPN
NA > All other
regions
A > LA
S3 > S1, T1.5, T2.5
-
Pervasive
entrenched
corruption
USA > BRA, CHN,
IND, ITA, RUS
CHE, JPN > BRA,
IND, ITA, RUS
CHN, DEU, GBR >
IND, ITA, RUS
NA > A, E, LA, SSA
A, E, MENA > LA,
SSA
S3 > All other
stages
S2, T2.5 > S1
-
2.72
<
Terrorism
CHN > IND, ITA, JPN,
RUS
USA > IND, JPN,
RUS
E, NA, MENA > LA,
SSA
A > LA
S3 > S1, T1.5, T2.5
S2, T2.5 > S1
-
3.01
Unilateral
resource
nationalization
BRA, CHN, USA >
DEU, GBR, IND, ITA,
JPN
CHE > ITA, JPN
NA > A, E, LA, SSA
T2.5, S3 > S1
-
Widespread illicit
trade
CHN, USA > ITA,
RUS
NA > E, LA, SSA
A > LA, SSA
E, MENA > SSA
S3 > All other
stages
S2 > S1
-
Backlash against
globalization
DEU > GBR, IND,
ITA, JPN
USA > JPN
S3 > S1, T1.5, S2
T2.5 > S1
-
72
Global Risks 2013
-
A, B > IO
3.13
<
3.27
-
3.26
>
3.09
-
2.88
>
2.72
-
3.11
>
2.88
-
-
-
-
-
-
-
-
-
2.97
-
-
<
3.16
-
-
2.89
<
3.12
-
-
2.98
<
3.13
-
-
-
3.17
>
3.04
Section 1
Food shortage
crises
BRA > GBR, IND,
JPN
CHE, CHN, DEU,
USA > IND, JPN
NA > A, MENA, LA,
SSA
E > A, SSA
A > SSA
T2.5, S3 > S1, T1.5,
S2
S2 > S1, T1.5
-
Ineffective illicit
drug policies
CHE, CHN > BRA,
GBR, ITA, RUS, USA
JPN > BRA, ITA,
RUS, USA
DEU > BRA, ITA
A > LA, NA, SSA
E, MENA > LA
S3 > S1, T1.5, T2.5
-
Mismanagement
of population
ageing
IND > GBR, ITA, RUS
CHE > ITA, RUS
MENA > NA, E
Rising rates of
chronic disease
JPN > BRA, GBR,
IND, RUS, USA
A > LA, SSA
E, NA, MENA >
SSA
S3 > All other
stages
S2 > S1
-
Rising religious
fanaticism
BRA, CHN > IND,
RUS, USA
CHE > IND, USA
JPN > IND
LA > E, MENA, NA,
SSA
S2 > S1, T1.5, S3
S3 > S1, T1.5
T2.5 > S1
-
3.06
<
Unmanaged
migration
BRA > IND, ITA, RUS
USA > IND, ITA
CHN > IND
NA > E
All other regions >
SSA
T2.5, S3 > S1, S2
T1.5, S2 > S1
-
2.91
Unsustainable
population
growth
CHE, CHN, USA >
IND
NA > A, SSA
E > SSA
T2.5, S3 > S1, T1.5
S2 > S1
-
2.89
Vulnerability to
pandemics
CHE, CHN, USA >
BRA, IND, RUS
DEU, JPN > IND, RUS
A, E, NA > LA, SSA
S3 > All other
stages
S2, T2.5 > S1
-
Water supply
crises
BRA > CHN, GBR,
IND, ITA, USA
CHE, DEU, JPN >
CHN, IND, ITA
CHN, GBR, RUS,
USA > IND
E > A, MENA, SSA
NA > A, SSA
LA > SSA
T2.5, S3 > S1, T1.5,
S2
S2 > S1
Critical systems
failure
USA > BRA, GBR,
IND, ITA, RUS
CHE > IND, ITA, RUS
NA > A, E, LA, SSA
A > LA, SSA
E, MENA > SSA
S3 > All other
stages
S2 > S1
-
-
Cyber attacks
USA > GBR, IND,
ITA, JPN, RUS
CHN > IND
NA > A, E, LA, SSA
A, E, MENA > SSA
S3 > All other
stages
S2, T2.5 > S1
-
Failure of
intellectual
property regime
USA > RUS
NA > LA, SSA,
MENA
S3 > All other
stages
-
Massive digital
misinformation
USA > IND, ITA, RUS
CHE, CHN > IND, ITA
DEU, GBR, JPN >
IND
NA > A, E, LA, SSA
A, E, MENA > SSA
S3 > All other
stages
S2, T2.5 > S1
B > IO
2.99
<
3.11
-
3.18
>
3.01
Massive incident
USA > BRA, GBR,
of data fraud/theft IND, ITA, RUS
NA > A, E, LA, SSA
A > LA, SSA
E, MENA > SSA
S3 > All other
stages
-
2.88
<
3.04
-
3.13
>
2.91
Mineral resource
supply
vulnerability
USA > DEU, GBR,
IND, ITA, JPN
CHN, RUS > GBR,
IND, ITA, JPN
NA > All other
regions
T2.5, S3 > S1, T1.5
S2 > S1
-
2.85
<
3.01
-
Proliferation of
orbital debris
USA > BRA, GBR,
IND, ITA, JPN
CHN > BRA
NA > All other
regions
A > LA
S3 > S1, S2, T2.5
-
-
-
Unforeseen
consequences of
climate change
mitigation
JPN > GBR, IND
CHN, USA > GBR
NA > LA, SSA
S3 > All other
stages
-
-
-
Unforeseen
consequences of
nanotechnology
USA > BRA, GBR,
IND
CHN, JPN > BRA
NA > E, LA, MENA,
SSA
A > LA, MENA, SSA
Europe > LA, SSA
S3 > All other
stages
-
-
Unforeseen
consequences of
new life science
technologies
USA > BRA, GBR,
ITA, RUS
NA > E, LA, SSA,
MENA
A, E > LA, SSA
S3 > All other
stages
-
-
3.38
-
-
2.81
<
2.95
-
<
-
-
-
-
>
2.82
3.19
3.19
>
2.99
<
3.13
3.08
>
2.89
2.94
<
3.10
<
3.21
3.10
>
2.95
2.99
<
3.12
<
2.87
3.27
>
2.99
-
-
3.25
<
3.39
2.98
-
3.1
3.21
Section 3
G, A, B > N
<
Section 2
-
3.23
-
2.97
<
3.31
-
3.14
>
2.87
-
-
3.11
>
2.93
-
-
Section 4
3.03
2.82
-
-
2.84
>
Section 6
<
>
Section 5
2.64
2.77
-
2.67
-
2.62
2.92
>
2.65
2.85
>
2.70
Global Risks 2013
73
Section 1
Acknowledgements
Section 2
Section 3
Section 4
Global Risks 2013 synthesises the insights,
ideas and contributions of many individuals
through workshops, interviews, group calls
and research. The project team sincerely
thanks everyone who took part in the
challenge to think hard about global risks.
Without their dedication, guidance and
support, we would not have been able to
develop this report.
Global Risks 2013, Eighth Edition Partners
Marsh & McLennan Companies
National University of Singapore
Oxford Martin School, University of Oxford
Swiss Reinsurance Company
Wharton Center for Risk Management, University of
Pennsylvania
Zurich Insurance Group
With special thanks to Advisory Group for the Global Risks
2013 Eighth Edition (in alphabetical order by last name):
David Cole, Swiss Reinsurance Company
John P. Drzik, Oliver Wyman Group (MMCo)
Ian Goldin, Oxford Martin School
Howard Kunreuther, The Wharton School, University of
Pennsylvania
Section 5
Axel Lehmann, Zurich Insurance Group
Tan Chorh Chuan, National University of Singapore
And the following representatives of the global risk partners
for their contribution to the Global Risks report content
development and dissemination (in alphabetical order by last
name):
Josephine Chennell, Swiss Reinsurance Company
Section 6
Natalie Day, Oxford Martin School
Rainer Egloff, Swiss Reinsurance Company
Ho Tech Hua, National University of Singapore
Erwann Michel-Kerjan, The Wharton School, University of
Pennsylvania
Lucy Nottingham, Marsh & McLennan Companies
Gregory Renand, Zurich Insurance Group
Reto Schneider, Swiss Reinsurance Company
Andrea Stuermer, Zurich Insurance Group
Tay Lee Teng, National University of Singapore
Mike Useem, The Wharton School, University of Pennsylvania
Steve Wilson, Zurich Insurance Group
Alex Wittenberg, Marsh & McLennan Companies
74
Global Risks 2013
Section 1
The project team would also like to thank all the business,
public sector, academic and civil society leaders who
participated in our interviews, workshops, and risk cases
development (in alphabetical order by last name with their
affiliation at the time of participation):
Tikki Pang, National University of Singapore
Dapo Akande, Oxford Martin School
Anders Sandberg, Oxford Martin School
Mark Ames, Oliver Wyman (Marsh & McLennan Companies)
Julian Savulescu, Oxford Martin School
Daniel Andris, Swiss Reinsurance Company
Oliver Schelske, Swiss Reinsurance Company
Dan Awrey, University of Oxford
Andreas Schraft, Swiss Reinsurance Company
Valerio Bacak, The Wharton School, University of Pennsylvania
Martin Schürz, Swiss Reinsurance Company
Luis Ballesteros, The Wharton School, University of
Pennsylvania
Lutfey Siddiqi, National University of Singapore
John Boochever, Oliver Wyman (Marsh & McLennan
Companies)
Richard Smith-Bingham, Oliver Wyman (Marsh & McLennan
Companies)
Sandra Burmeier, Swiss Reinsurance Company
Keoyong Song, The Wharton School, University of Pennsylvania
Philippe Brahin, Swiss Reinsurance Company
Yumiko Takada, Marsh Japan Inc (Marsh & McLennan Companies)
Jerry Cacciotti, Oliver Wyman (Marsh & McLennan Companies)
Rolf Tanner, Swiss Reinsurance Company
Iordanis Chatziprodromou, Swiss Reinsurance Company
Dodo J. Thampapillai, National University of Singapore
Oliver Chen, National University of Singapore
Cecilia Tortajada, International Water Resources Association
Carl Frey, Oxford Martin School
Ginger Turner, The Wharton School, University of Pennsylvania
Tim Garton Ash, University of Oxford
Sonia Trigueros, Oxford Martin School
Ed George, The Wharton School, University of Pennsylvania
Richard Waterman, The Wharton School, University of
Pennsylvania
Raja Hafiz Affandi, The Wharton School, University of
Pennsylvania
Peter Hausmann, Swiss Reinsurance Company
Carol Heller, The Wharton School, University of Pennsylvania
Claus Herbolzheimer, Oliver Wyman (Marsh & McLennan
Companies)
Michael Weissel, Oliver Wyman (Marsh & McLennan
Companies)
Daniel Wesemann, Swiss Reinsurance Company
Martin Weymann, Swiss Reinsurance Company
Barrie Wilkinson, Oliver Wyman (Marsh & McLennan
Companies)
Ngaire Woods, Blavatnik School of Government
Arran Yentob, Oliver Wyman (Marsh & McLennan Companies)
Bernard Yeung, National University of Singapore
Satoru Hiraga, Marsh Japan (Marsh & McLennan Companies)
Nick Wildgoose, Zurich Insurance Group
Yoshiki Hiruma, Development Bank of Japan
Kurt Karl, Swiss Reinsurance Company
Jussi Keppo, National University of Singapore
Heng Yee Kuang, National University of Singapore
Tim Kruger, Oxford Martin School
Susan Lea, Oxford Martin School
George Leeson, Oxford Martin School
Elizabeth Leicht, Oxford Martin School
Alexander Leveringhaus, Oxford Martin School
Michael Lierow, Oliver Wyman (Marsh & McLennan Companies)
John Merkovsky, Marsh Inc (Marsh & McLennan Companies)
Ann Miller, The Wharton School, University of Pennsylvania
Lea Müller, Swiss Reinsurance Company
Mary Ng Mah Lee, National University of Singapore
Kalypso Nicolaidis, University of Oxford
David Bresch, Swiss Reinsurance Company
Davis Cherry, Global Adaptation Institute
Megan Clark, Commonwealth Scientific and Industrial Research
Organisation
Juan José Daboub, Global Adaptation Institute
Charlotta Groth, Zurich Insurance Group
Jim W Hall, Environmental Change Institute, University of Oxford
Abyd Karmali, Bank of America Merrill Lynch
Signe Krogstrup, Swiss National Bank
Marc Levy, CIESIN, Columbia University
Manuel Lewin, Zurich Insurance Group
Anders Lyngaa Kristoffersen, Novozymes
Murray Birt, Deutsche Bank Group
Guy Miller, Zurich Insurance Group
Chandran Nair, Global Institute for Tomorrow
Ian Noble, Global Adaptation Institute
Toby Ord, Oxford Martin School
Global Risks 2013
75
Section 6
Mike King, NERA, Oliver Wyman (Marsh & McLennan
Companies)
Section 5
Anwarul Hasan, Swiss Reinsurance Company
Janet Smart, University of Oxford
Section 4
Beat Habegger, Swiss Reinsurance Company
Daniel Ryan, Swiss Reinsurance Company
Section 3
Mark Goh, National University of Singapore
Felix Reed-Tsochas, Oxford Martin School
Section 2
Charles Godfray, Oxford Martin School
Robert Parisi, Marsh Inc (Marsh & McLennan Companies)
Section 1
Konrad Otto-Zimmerman, ICLEI
Section 2
Tim Palmer, Oxford Martin School
Special Report: Building National Resilience to Global
Risks
Lindene Patton, Zurich Insurance Group
Ian Bremmer, Eurasia Group
Johan Rockström, Stockholm Resilience Centre
Dennis L. Chesley, PwC
Juan Carlos Castilla Rubio, Planetary Skin Institute
Mary Cline, Eurasia Group
John Scott, Zurich Insurance Group
Anne-Sophie Crépin, Stockholm Resilience Centre
Jorge E. Viñuales, The Graduate Institute, Geneva
Elizabeth Eide, The National Academies, Division of Earth and
Life Sciences
Victor Galaz, Stockholm Resilience Centre
Section 3
Jolyon Barker, Deloitte Touche Tomatsu Ltd
Jac C. Heckelman, Wake Forest University
Adam Bly, Seed
Emily Hoch, Eurasia Group
Sadie Creese, Oxford Martin School
Anders Hoffman, Danish Enterprise and Construction Authority
Scott David, University of Washington Law, Technology and Arts
Group
Randolph Kent, Humanitarian Futures Programme
Giorgos Dimitriou, European Network and Information Security
Agency (ENISA)
Emma Lindqvist, Eurasia Group
Szerb László, University of Pecs
Section 4
Daniel Eherer, Zurich Insurance Group
Alexsandra Lloyd, Eurasia Group
Nik Gowing, BBC World News
Kirstjen Nielsen, Sunesis Consulting, LLC
Witold Henisz, The Wharton School, University of Pennsylvania
Satoru Nishikawa, Japan Water Agency
Louis Marinos, European Network and Information Security
Agency (ENISA)
Sara Pantuliano, Overseas Development Institute
Matthew Prince, CloudFlare
Courtney Rickert McCaffrey, Eurasia Group
Andreas Sfakianakis, European Network and Information
Security Agency (ENISA)
Christopher Michaelson, PwC
Ray Stanton, British Telecom
Michaela Saisana, European Commission
Jamie Tomasello, CloudFlare
Andrea Saltelli, OECD
Ross D. Schaap, Eurasia Group
David B. Agus, University of Southern California
Rodrigo Pérez Mackenna, Ministerio de Vivienda y Urbanismo
Dionisis Philippas, JRC
Don Tapscott, Moxie Insights
Section 5
Lindsey Baden, The New England Journal of Medicine
X Factors
Richard Bergström, European Federation of Pharmaceutical
Industries and Associations
Tim Appenzeller, Nature
Philip Campbell, Nature
Zulfiqar A. Bhutta, The Aga Khan University
Otto Cars, ReAct - Action on Antibiotic Resistance
Jean Carlet, World Alliance against Antibiotic Resistance (WAAR)
Jeffrey M. Drazen, The New England Journal of Medicine
Section 6
John Frater, Oxford Martin School
Chris Gillies, Zurich Insurance Group
Kari Grave, European Medicines Agency
Martha Gyansa-Lutterodt, Pharmaceutical Services and Chief
Pharmacist of Ghana
Anna Hedin, ReAct - Action on Antibiotic Resistance Uppsala
University
Dominique L. Monnet, European Centre for Disease Prevention
and Control
Carmem Pessoa, World Health Organization
Laura J.V. Piddock, University of Birmingham and Antibiotic
Action
Paul Rogers, World Health Organization
Nabil Safrany, European Centre for Disease Prevention and
Control
Johan Struwe, World Health Organization
76
Global Risks 2013
We also would like to thank all the people who participated
in the Global Risks Survey 2012.
Section 1
In addition, the project team expresses its gratitude to the
Global Agenda Council community managers, the Business
Engagement and Development team, and the following
colleagues from the World Economic Forum for their advice
and support throughout the Global Risks report
development:
Viraj Mehta
Amrote Abdella
Martin Nägele
David Aikman
Navdeep
Guillaume Amigues
Lyuba Nazaruk
Marisol Argueta
Derek O’Halloran
Anastassia Aubakirova
Sushant Palakurthi Rao
Adeyemi Babington-Ashaye
Gary Phillips
Beñat Bilbao
Pengcheng Qu
Carl Björkman
Olivier Raynaud
Jennifer Blanke
Lucien Rieben
Roberto Bocca
Pedro Rodrigues De Almeida
Ciara Browne
Olivier Schwab
Giancarlo Bruno
Kate Seiler
Sophie Bussmann
Bernardo Silva
Roberto Crotti
Paul Smyke
Piers Cumberlege
Masao Takahashi
Nicholas Davis
Michael Tost
Margareta Drzeniek
Terri Toyota
Isabel de Sola
Akira Tsuchiya
Sean Doherty
Tran Tu-Trang
Michael Drexler
Silvia von Gunten
Miroslav Dusek
Nina Vugman
John Dutton
Regula Waltenspuel
Rim El Habibi
Dominic Waughray
Manal El Meligi
Bruce Weinelt
Cristiana Falcone
Tiffany West
Brindusa Fidanza
Alex Wong
Thierry Geiger
Founder and Executive Chairman
Liana Melchenko
Matthew Miller
Katherine Milligan
Section 2
John Moavenzadeh
Section 3
Section 4
Section 5
Martina Gmür
Ariane Haeni
Klaus Schwab
Managing Directors
Hala Hanna
Børge Brende
William Hoffman
Robert Greenhill
Antonio Human
Lee Howell
Alexandra Jequier
Adrian Monck
Julianne Jammers
Sarita Nayyar
Jeremy Jurgens
Gilbert Probst
Elsie Kanza
Jean-Pierre Rosso
Thomas Kerr
Kevin Steinberg
Hanseul Kim
Alois Zwinggi
Section 6
Andrew Hagan
Pawel Konzal
Rodolfo Lara Torres
Helena Leurent
Alan Marcus
Global Risks 2013
77
Section 1
Project Team
Section 2
Section 3
The Global Risks 2013 report, Eighth
Edition, team includes the following
World Economic Forum staff members:
Editor in Chief
Production Team
Lee Howell, Managing Director, Member of the Managing Board
Michael Hanley, Editorial Director, Communications
Kamal Kimaoui, Director, Head of Production and Design
Section 4
Research Team, Global Risks Report
Chiemi Hayashi, Director, Head of Risk Response Network and
Risk Research
Catherine Zwahlen, Senior Knowledge Manager
David Gleicher, Manager, Qualitative Research
Scott David, Associate Director, Head of Information Interaction
Adrian Shawcross, Freelance Graphic Designer
David Bustamante, Senior Content Producer, Publication and
Design
Floris Landi, Graphic Designer, Publication and Design
Section 5
Florian Ramseger, Manager, Quantitative Research
David Helmsley, Junior Graphic Designer, Publication and
Design
Amey Soo, Research Associate, Quantitative Research
Mary Bridges, Editor
Katarina Hruba, Project Associate, Qualitative Research
Itonics GmbH, Web Design, Online Data Explorer
Karen Campbell, Senior Economist
Yoren Geromin, Graphic Design
Andrew Wright, Freelance Writer
Risk Response Network Team
Linda Freiner, Associate Director, Head of Community
Engagement
Section 6
Samantha Tonkin, Associate Director, Head of Communication
Navitri Putri Guillaume, Government Engagement Manager
Charles Lane, Supply Chain and Transport Risks Project
Manager
Alexis Munier, Editorial Manager
Ceri Parker, Writer
Edward Simmons, Resilience Practices Exchange Project
Manager
David Connolly, Business Engagement, Senior Community
Associate
Gregory Coudrier, Digital Associate
Rim El Habibi, Media Associate
Stéphanie Badawi, Team Coordinator
78
Global Risks 2013
The World Economic Forum
is an independent international
organization committed to
improving the state of the world
by engaging business, political,
academic and other leaders of
society to shape global, regional
and industry agendas.
Incorporated as a not-for-profit
foundation in 1971 and
headquartered in Geneva,
Switzerland, the Forum is
tied to no political, partisan
or national interests.
91-93 route de la Capite
CH-1223 Cologny/Geneva
Switzerland
Tel +41 (0) 22 869 1212
Fax +41 (0) 22 786 2744
contact@weforum.org
www.weforum.org

Global Risks Report 2013

Transcription

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